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Replicability-Index
Improving the replicability of empirical research
The Validation Crisis in Psychology
Ioannidis is Wrong Most of the Time
Replicability Rankings of 120 Psychology Journals (2010-2019)
A Meta-Psychological Perspective on the Decade of Replication Failures in Social Psychology
Z-Curve.2.0
A Quick Fix for the Replication Crisis in Psychology
Personalized P-Values for 200+ Social/Personality Psychologists
Tag Archives: Z-Curve
Open Discussion Forum: [67] P-curve Handles Heterogeneity Just Fine
March 25, 2018 UncategorizedFalse Positive Psychology, False-Facts, Leif Nelson, P-Curve, Post-Hoc-Power, Powergraphs, replicability, Uri Simonsohn, Z-CurveUlrich Schimmack
[67] P-curve Handles Heterogeneity Just Fine
UPDATE 3/27/2018: Here is R-code to see how z-curve and p-curve work and to run the simulations used by Datacolada and to try other ones. (R-Code download)
The blog Datacolada is a joint blog by Uri Simonsohn, Leif Nelson, and Joe Simmons. Like this blog, Datacolada blogs about statistics and research methods in the social sciences with a focus on controversial issues in psychology. Unlike this blog, Datacolada does not have a comments section. However, this shouldn't stop researchers to critically examine the content of Datacolada. As I have a comments section, I will first voice my concerns about blog post [67] and then open the discussion to anybody who cares about estimating the average power of studies that reported a "discovery" in a psychology journal.
Estimating power is easy when all studies are honestly reported. In this ideal world, average power can be estimated by the percentage of significant results and with the median observed power (Schimmack, 2015). However, in reality not all studies are published and researchers use questionable research practices that inflate success rates and observed power. Currently two methods promise to correct for these problems and to provide estimates of the average power of studies that yielded a significant result.
Uri Simonsohn's P-Curve has been in the public domain in the form of an app since January 2015. Z-Curve has been used to critique published studies and individual authors for low power in their published studies on blog posts since June 2015. Neither method has the stamp of approval of peer-review. P-Curve has been developed from Version 3.0 to Version 4.6 without presenting any simulations that the method works. It is simply assumed that the method works because it is built on a peer-reviewed method for the estimation of effect sizes. Jerry Brunner and I have developed four methods for the estimation of average power in a set of studies selected for significance, including z-curve and our own version of p-curve that estimates power and not effect sizes .
We have carried out extensive simulation studies and asked numerous journals to examine the validity of our simulation results. We also posted our results in a blog post and asked for comments. The fact that our work is still not published in 2018 does not reflect problems with out results. The reasons for rejection were mostly that it is not relevant to estimate average power of studies that have been published.
Respondents to an informal poll in the Psychological Methods Discussion Group mostly disagree and so do we.
There are numerous examples on this blog that show how this method can be used to predict that major replication efforts will fail (ego-depletion replicability report) or that claims about the way people (that is you and I) think in a popular book (Thinking: Fast and Slow) for a general audience (again that is you and me) by a Nobel Laureate are based on studies that were obtained with deceptive research practices.
The author, Daniel Kahneman, was as dismayed as I am by the realization that many published findings that are supposed to enlighten us have provided false facts and he graciously acknowledged this.
"I accept the basic conclusions of this blog. To be clear, I do so (1) without expressing an opinion about the statistical techniques it employed and (2) without stating an opinion about the validity and replicability of the individual studies I cited. What the blog gets absolutely right is that I placed too much faith in underpowered studies." (Daniel Kahneman).
It is time to ensure that methods like p-curve and z-curve are vetted by independent statistical experts. The traditional way of closed peer review in journals that need to reject good work because for-profit publishers and organizations like APS need to earn money from selling print-copies of their journals has failed.
Therefore we ask statisticians and methodologists from any discipline that uses significance testing to draw inferences from empirical studies to examine the claims in our manuscript and to help us to correct any errors. If p-curve is the better tool for the job, so be it.
It is unfortunate that the comparison of p-curve and z-curve has become a public battle. In an idealistic world, scientists would not be attached to their ideas and would resolve conflicts in a calm exchange of arguments. What better field to reach consensus than math or statistics where a true answer exists and can be revealed by means of mathematical proof or simulation studies.
However, the real world does not match the ideal world of science. Just like Uri-Simonsohn is proud of p-curve, I am proud of z-curve and I want z-curve to do better. This explains why my attempt to resolve this conflict in private failed (see email exchange).
The main outcome of the failed attempt to find agreement in private was that Uri Simonsohn posted a blog on Datacolada with the bold claim "P-Curve Handles Heterogeneity Just Fine," which contradicts the claims that Jerry and I made in the manuscript that I sent him before we submitted it for publication. So, not only did the private communication fail. Our attempt to resolve disagreement resulted in an open blog post that contradicted our claims. A few months later, this blog post was cited by the editor of our manuscript as a minor reason for rejecting our comparison of p-curve and z-curve.
Just to be clear, I know that the datacolada post that Nelson cites was posted after your paper was submitted and I'm not factoring your paper's failure to anticipate it into my decision (after all, Bem was wrong (Dan Simons, Editor of AMMPS)
Please remember, I shared a document and R-Code with simulations that document the behavior of p-curve. I had a very long email exchange with Uri Simonsohn in which I asked him to comment on our simulation results, which he never did. Instead, he wrote his own simulations to convince himself that p-curve works.
The tweet below shows that Uri is aware of the problem that statisticians can use statistical tricks, p-hacking, to make their method look better than they are.
I will now demonstrate that Uri p-hacked his simulations to make p-curve look better than it is and to hide the fact that z-curve is the better tool for the job.
Critical Examination of Uri Simonsohn's Simulation Studies
On the blog, Uri Simonsohn shows the Figure below which was based on an example that I provided during our email exchange. The Figure shows the simulated distribution of true power. It also shows the the mean true power is 61%, whereas the p-curve estimate is 79%. Uri Simonssohn does not show the z-curve estimate. He also does not show what the distribution of observed t-values looks like. This is important because few readers are familiar with histograms of power and the fact that it is normal for power to pile up at 1 because 1 is the upper limit for power.
I used the R-Code posted on the Datacolada website to provide additional information about this example. Before I show the results it is important to point out that Uri Simonshon works with a different selection model than Jerry and I. We verified that this has no implications for the performance of p-curve or z-curve, but it does have implications for the distribution of true power that we would expect in real data.
Selection for Significance 1: Jerry and I work with a simple model where researchers conduct studies, test for significance, and then publish the significant results. They may also publish the non-significant results, but they cannot be used to claim a discovery (of course, we can debate whether a significant result implies a discovery, but that is irrelevant here). We use z-curve to estimate the average power of those studies that produced a significant result. As power is the probabilty of obtaining a significant result, the average true power of significant results predicts the success rate in a set of exact replication studies. Therefore, we call this estimate an estimate of replicability.
Selection for Significance 2: The Datacolada team famously coined the term p-hacking. p-hacking refers to massive use of questionable research practices in order to produce statistically significant results. In an influential article, they created the impression that p-hacking allows researchers to get statistical significance in pretty much every study without a real effect (i.e., a false positive). If this were the case, researchers would not have failed studies hidden away like our selection model implies.
No File Drawers: Another Unsupported Claim by Datacolada
In the 2018 volume of Annual Review of Psychology (edited by Susan Fiske), the Datacolada team explicitly claims that psychology researchers do not have file drawers of failed studies.
There is an old, popular, and simple explanation for this paradox. Experiments that work are sent to a journal, whereas experiments that fail are sent to the file drawer (Rosenthal 1979). We believe that this "file-drawer explanation" is incorrect. Most failed studies are not missing. They are published in our journals, masquerading as successes.
They provide no evidence for this claim and ignore evidence to the contrary. For example, Bem (2011) pointed out that it is a common practice in experimental social psychology to conduct small studies so that failed studies can be dismissed as "pilot studies." In addition, some famous social psychologists have stated explicitly that they have a file drawer of studies that did not work.
"We did run multiple studies, some of which did not work, and some of which worked better than others. You may think that not reporting the less successful studies is wrong, but that is how the field works." (Roy Baumeister, personal email communication)
In response to replication failures, Kathleen Vohs acknowledged that a couple of studies with non-significant results were excluded from the manuscript submitted for publication that was published with only significant results.
(2) With regard to unreported studies, the authors conducted two additional money priming studies that showed no effects, the details of which were shared with us.
(quote from Rohrer et al., 2015, who failed to replicate Vohs's findings; see also Vadillo et al., 2016.)
Dan Gilbert and Timothy Wilson acknowledged that they did not publish non-significant results that they considered to be uninformative.
"First, it's important to be clear about what "publication bias" means. It doesn't mean that anyone did anything wrong, improper, misleading, unethical, inappropriate, or illegal. Rather it refers to the wellknown fact that scientists in every field publish studies whose results tell them something interesting about the world, and don't publish studies whose results tell them nothing. Let us be clear: We did not run the same study over and over again until it yielded significant results and then report only the study that "worked." Doing so would be clearly unethical. Instead, like most researchers who are developing new methods, we did some preliminary studies that used different stimuli and different procedures and that showed no interesting effects. Why didn't these studies show interesting effects? We'll never know. Failed studies are often (though not always) inconclusive, which is why they are often (but not always) unpublishable. So yes, we had to mess around for a while to establish a paradigm that was sensitive and powerful enough to observe the effects that we had hypothesized." (Gilbert and Wilson).
Bias analyses show some problems with the evidence for stereotype threat effects. In a radio interview, Michael Inzlicht reported that he had several failed studies that were not submitted for publication and he is now skeptical about the entirely stereotype threat literature (conflict of interest: Mickey Inzlicht is a friend and colleague of mine who remains the only social psychologists who has published a critical self-analysis of his work before 2011 and is actively involved in reforming research practices in social psychology).
Steve Spencer also acknowledged that he has a file drawer with unsuccessful studies. In 2016, he promised to open his file-drawer and make the results available.
By the end of the year, I will certainly make my whole file drawer available for any one who wants to see it. Despite disagreeing with some of the specifics of what Uli says and certainly with his tone I would welcome everyone else who studies stereotype threat to make their whole file drawer available as well.
Nearly two years later, he hasn't followed through on this promise (how big can it be? LOL).
Although this anecdotal evidence makes it clear that researchers have file drawers with non-significant results, it remains unclear how large file-drawers are and how often researchers p-hacked null-effects to significance (creating false positive results).
The Influence of Z-Curve on the Distribution of True Power and Observed Test-Statistics
Z-Curve, but not p-curve, can address this question to some extent because p-hacking influences the probability that a low-powered study will be published. A simple selection model with alpha = .05 implies that only 1 out of 20 false positive results produces a significant result and will be included in the set of studies with significant results. In contrast, extreme p-hacking implies that every false positive result (20 out of 20) will be included in the set of studies with significant results.
To illustrate the implications of selection for significance versus p-hacking, it is instructive to examine the distribution of observed significant results based on the simulated distribution of true power in Figure 1.
Figure 2 shows the distribution assuming that all studies will be p-hacked to significance. P-hacking can influence the observed distribution, but I am assuming a simple p-hacking model that is statistically equivalent to optional stopping with small samples. Just keep repeating the experiment (with minor variations that do not influence power to deceive yourself that you are not p-hacking) and stop when you have a significant result.
The histogram of t-values looks very similar to a z-score because t-values with df = 98 are approximately normally distributed. As all studies were p-hacked, all studies are significant with qt(.975,98) = 1.98 as criterion value. However, some studies have strong evidence against the null-hypothesis with t-values greater than 6. The huge pile of t-values just above the criterion value of 1.98 occurs because all low powered studies became significant.
The distribution in Figure 3 looks different than the distribution in Figure 2.
Now there are numerous non-significant results and even a few significant results with the opposite sign of the true effect (t < -1.98). For the estimation of replicability only the results that reached significance are relevant, if only for the reason that they are the only results that are published (success rates in psychology are above 90%; Sterling, 1959, see also real data later on). To compare the distributions it is more instructive to select only the significant results in Figure 3 and to compare the densities in Figures 2 and 3.
The graph in Figure 4 shows that p-hacking results in more just significant results with t-values between 2 and 2.5 than mere publication bias does. The reason is that the significance filter of alpha = .05 eliminates false positives and low powered true effects. As a result the true power of studies that produced significant results is higher in the set of studies that were selected for significance. The average true power of the honest significant results without p-hacking is 80% (as seen in Figure 1, the average power for the p-hacked studies in red is 61%).
With real data, the distribution of true power is unknown. Thus, it is unknown how much p-hacking occurred. For the reader of a journal that reports only significant it is also irrelevant whether p-hacking occurred. A result may be reported because 10 similar studies tested a single hypothesis or 10 conceptual replication studies produced 1 significant result. In either scenario, the reported significant result provides weak evidence for an effect if the significant result occurred with low power.
It is also important to realize (and it took Jerry and I some time to convince ourselves with simulations that this is actually true) that p-curve and z-curve estimates do not depend on the selection mechanism. The only information that matters is the true power of studies and not how studies were selected. To illustrate this fact, I also used p-curve and z-curve to estimate the average power of the t-values without p-hacking (blue distribution in Figure 4). P-Curve again overestimates true power. While average true power is 80%, the p-curve estimate is 94%.
In conclusion, the datacolada blog post did present one out of several examples that I provided and that were included in the manuscript that I shared with Uri. The Datacolada post correctly showed that z-curve provides good estimates of the average true power and that p-curve produces inflated estimates.
I elaborated on this example by pointing out the distinction between p-hacking (all studies are significant) and selection for significance (e.g., due to publication bias or in assessing replicability of published results). I showed that z-curve produces the correct estimates with and without p-hacking because the selection process does not matter. The only consequence of p-hacking is that more low-powered studies become significant because it undermines the function of the significance filter to prevent studies with weak evidence from entering the literature.
In conclusion, the actual blog post shows that p-curve can be severely biased when data are heterogeneous, which contradicts the title that P-Curve handles heterogeneity just fine.
When The Shoe Doesn't Fit, Cut of Your Toes
To rescue p-curve and to justify the title, Uri Simonsohn suggests that the example that I provided is unrealistic and that p-curve performs as well or better in simulations that are more realistic. He does not mention that I also provided real world examples in my article that showed better performance of z-curve with real data.
So, the real issue is not whether p-curve handles heterogeneity well (it does not). The real issue is now how much heterogeneity we should expect.
Figure 5 shows that Uri Simonsohn considers to be realistic data. The distribution of true power uses the same beta distribution as the distribution in Figure 1, but instead of scaling it from the lowest possible value (alpha = 5%) to the highest possible value 1-1/infinity), it scales power from alpha to a maximum of 80%. For readers less familiar with power, a value of 80% implies that researches plan studies deliberately with the risk of a 20% probability to end up with a false negative result (i.e., the effect exists, but the evidence is not strong enough, p > .05).
The labeling in the graph implies that studies with more than recommended 80% power, including 81% power are considered to have extremely high power (again, with a 20% risk of a false positive result). The graph also shows that p-curve provided an unbiased estimate of true average power despite (extreme) heterogeneity in true power between 5% and 80%.
Figure 6 shows the histogram of observed t-values based on a simulation in which all studies in Figure 5 are p-hacked to get significance. As p-hacking inflates all t-values to meet the minimum value of 1.98, and truncation of power to values below 80% removes high t-values, 92% of t-values are within the limited range from 1.98 to 4. A crud measure of heterogeneity is the variance of t-values, which is 0.51. With N = 100, a t-distribution is just a little bit wider than the standard normal distribution, which has a standard deviation of 1. Thus, the small variance of 0.51 indicates that these data have low variability.
The histogram of observed t-values and the variance in these observed t-values makes it possible to quantify heterogeneity in true power. In Figure 2, heterogeneity was high (Var(t) = 1.56) and p-curve overestimated average true power. In Figure 6, heterogeneity is low (Var(t) = 0.51) and p-curve provided accurate estimates. This finding suggests that estimation bias in p-curve is linked to the distribution and variance in observed t-values, which reflects the distribution and variance in true power.
When the data are not simulated, test statistics can come from different tests with different degrees of freedom. In this case, it is necessary to convert all test statistics into z-scores so that strength of evidence is measured in a common metric. In our manuscript, we used the variance of z-scores to quantify heterogeneity and showed that p-curve overestimates when heterogeneity is high.
In conclusion, Uri Simonsohn demonstrated that p-curve can produce accurate estimates when the range of true power is arbitrarily limited to values below 80% power. He suggests that this is reasonable because having more than 80% power is extremely high power and rare.
Thus, there is no disagreement between Uri Simonsohn and us when it comes to the statistical performance of p-curve and z-curve. P-curve overestimates when power is not truncated at 80%. The only disagreement concerns the amount of actual variability in real data.
What is realistic?
Jerry and I are both big fans of Jacob Cohen who has made invaluable contributions to psychology as a science, including his attempt to introduce psychologists to Neyman-Pearson's approach to statistical inferences that avoids many of the problems of Fishers' approach that dominates statistics training in psychology to this day.
The concept of statistical power requires that researchers formulate an alternative hypothesis, which requires specifying an expected effect size. To facilitate this task, Cohen developed standardized effect sizes. For example, Cohen's standardizes a mean difference (e.g., height difference between men and women in centimeters) by the standard deviation. As a result, the effect size is independent of the unit of measurement and is expressed in terms of percentages of a standard deviation. Cohen provided rough guidelines about the size of effect sizes that one could expect in psychology.
It is now widely accepted that most effect sizes are in the range between 0 and 1 standard deviation. It is common to refer to effect sizes of d = .2 (20% of a standard deviation) as small, d = .5 as medium, and d = .8 as large.
True power is a function of effect size and sampling error. In a between subject study sampling error is a function of sample size and most sample sizes in between-subject designs fall into a range from 40 to 200 participants, although sample sizes have been increasing somewhat in response to the replication crisis. With N = 40 to 200, sampling error ranges from 0.14 (2/sqrt(200) to .32 (2/sqrt(40).
The non-central t-values are simply the ratio of standardized effect sizes and sampling error of standardized measures. At the lowest end, effect sizes of 0 have a non-central t-value of 0 (0/.14 = 0; 0/.32 = 0). At the upper end, a large effect size of .8 obtained in the largest sample (N = 200) yields a t-value of .8/.14 = 5.71. While smaller non-central t-values than 0 are not possible, larger non-central t-values can occur in some studies. Either the effect size is very large or sampling error is smaller. Smaller sampling errors are especially likely when studies use covariates, within-subject designs or one-sample t-tests. For example, a moderate effect size (d = .5) in a within-subject design with 90% fixed error variance (r = .9), yields a non-central t-value of 11.
A simple way to simulate data that are consistent with these well-known properties of results in psychology is to assume that the average effect size is half a standard deviation (d = .5) and to model variability in true effect sizes with a normal distribution with a standard deviation of SD = .2. Accordingly, 95% of effect sizes would fall into the range from d = .1 to d = .9. Sample sizes can be modeled with a simple uniform distribution (equal probability) from N = 40 to 200.
Converting the non-centrality parameters to power with p < .05 shows that many values fall into the region from .80 to 1 that Uri Simonsohn called extremely high power. The graph shows that it does not require extremely large effect sizes (d > 1) or large samples (N > 200) to conduct studies with 80% power or more. Of course, the percentage of studies with 80% power or more depends on the distribution of effect sizes, but it seems questionable to assume that studies rarely have 80% power.
The mean true power is 66% (I guess you see where this is going).
This is the distribution of the observed t-values. The variance is 1.21 and 23% of the t-values are greater than 4. The z-curve estimate is 66% and the p-curve estimate is 83%.
In conclusion, a simulation that starts with knowledge about effect sizes and sample sizes in psychological research shows that it is misleading to call 80% power or more extremely high power that is rarely achieved in actual studies. It is likely that real datasets will include studies with more than 80% power and that this will lead p-curve to overestimate average power.
A comparison of P-Curve and Z-Curve with Real Data
The point of fitting p-curve and z-curve to real data is not to validate the methods. The methods have been validated in simulation studies that show good performance of z-curve and poor performance of p-curve when hterogeneity is high.
The only question remains how biased p-curve is with real data. Of course, this depends on the nature of the data. It is therefore important to remember that the Datacolada team proposed p-curve as an alternative to Cohen's (1962) seminal study of power in the 1960 issue of the Journal of Abnormal and Social Psychology.
"Estimating the publication-bias corrected estimate of the average power of a set of studies can be useful for at least two purposes. First, many scientists are intrinsically
interested in assessing the statistical power of published research (see e.g., Button et al., 2013; Cohen, 1962; Rossi, 1990; Sedlmeier & Gigerenzer, 1989).
There have been two recent attempts at estimating the replicability of results in psychology. One project conducted 100 actual replication studies (Open Science Collaboration, 2015). A more recent project examined the replicability of social psychology using a larger set of studies and statistical methods to assess replicability (Motyl et al., 2017).
The authors sampled articles from four journals, the Journal of Personality and Social Psychology, Personality and Social Psychology Bulletin, Journal of Experimental Psychology, and Psychological Science and four years, 2003, 2004, 2013, and 2014. They randomly sampled 543 articles that contained 1,505 studies. For each study, a coding team picked one statistical test that tested the main hypothesis. The authors converted test-statistics into z-scores and showed histograms for the years 2003-2004 and 2013-2014 to examine changes over time. The results were similar.
The histograms show clear evidence that non-significant results are missing either due to p-hacking or publication bias. The authors did not use p-curve or z-curve to estimate the average true power. I used these data to examine the performance of z-curve and p-curve. I selected only tests that were coded as ANOVAs (k = 751) or t-tests (k = 232). Furthermore, I excluded cases with very large test statistics (> 100) and experimenter degrees of freedom (10 or more). For participant degrees of freedom, I excluded values below 10 and above 1000. This left 889 test statistics. The test statistics were converted into z-scores. The variance of the significant z-scores was 2.56. However, this is due to a long tail of z-scores with a maximum value of 18.02. The variance of z-scores between 1.96 and 6 was 0.83.
Fitting z-curve to all significant z-scores yielded an estimate of 45% average true power. The p-curve estimate was 78% (90%CI = 75;81). This finding is not surprising given the simulation results and the variance in the Motyl et al. data.
One possible solution to this problem could be to modify p-curve in the same way that z-curve only models z-scores between 1.96 and 6 and treats all z-scores of 6 as having power = 1. The z-curve estimate is then adjusted by the proportion of extreme z-scores
average.true.power = z-curve.estimate * (1 – extreme) + extreme
Using the same approach with p-curve does help to reduce the bias in p-curve estimates, but p-curve still produces a much higher estimate than z-curve, namely 63% (90%CI = .58;67. This is still nearly 20% higher than the z-curve estimate.
In response to these results, Leif Nelson argued that the problem is not with p-curve, but with the Motyl et al. data.
They attempt to demonstrate the validity of the Z-curve with three sets of clearly invalid data.
One of these "clearly invalid" data are the data from Motyl et al.'s study. Nelson claim is based on another datacolada blog post about the Motyl et al. study with the title
[60] Forthcoming in JPSP: A Non-Diagnostic Audit of Psychological Research
A detailed examination of datacolada 60 will be the subject of another open discussion about Datacolada. Here it is sufficient to point that Nelson's strong claim that Motyl et al.'s data are "clearly invalid" is not based on empirical evidence. It is based on disagreement about the coding of 10 out of over 1,500 tests (0.67%). Moreover, it is wrong to label these disagreements mistakes because there is no right or wrong way to pick one test from a set of tests.
In conclusion, the Datacolada team has provided no evidence to support their claim that my simulations are unrealistic. In contrast, I have demonstrated that their truncated simulation does not match reality. Their only defense is now that I cheery-picked data that make z-curve look good. However, a simulation with realistic assumptions about effect sizes and sample sizes also shows large heterogeneity and p-curve fails to provide reasonable estimates.
The fact that sometimes p-curve is not biased is not particularly important because z-curve provides practically useful estimates in these scenarios as well. So, the choice is between one method that gets it right sometimes and another method that gets it right all the time. Which method would you choose?
It is important to point out that z-curve shows some small systematic bias in some situations. The bias is typically about 2% points. We developed a conservative 95%CI to address this problem and demonstrated that his 95% confidence interval has good coverage under these conditions and is conservative in situations when z-curve is unbiased. The good performance of z-curve is the result of several years of development. Not surprisingly, it works better than a method that has never been subjected to stress-tests by the developers.
Z-curve has many additional advantages over p-curve. First, z-curve is a model for heterogeneous data. As a result, it is possible to develop methods that can quantify the amount of variability in power while correcting for selection bias. Second, heterogeneity implies that power varies across studies. As studies with higher power tend to produce larger z-scores, it is possible to provide corrected power estimates for sets of z-values. For example, the average power of just significant results (z < 2.5) could be very low.
Although these new features are still under development, first tests show promising results. For example, the local power estimates for Motyl et al. suggest that test statistics with z-scores below 2.5 (p = .012) have only 26% power and even those between 2.5 and 3.0 (p = .0026) have only 34% power. Moreover, test statistics between 1.96 and 3 account for two-thirds of all test statistics. This suggests that many published results in social psychology will be difficult to replicate.
The problem with fixed-effect models like p-curve is that the average may be falsely generalized to individual studies. Accordingly, an average estimate of 45% might be misinterpreted as evidence that most findings are replicable and that replication studies with a little bit power would be able to replicate most findings. However, this is not the case (OSC, 2015). In reality, there are many studies with low power that are difficult to replicate and relatively few studies with very high power that are easy to replicate. Averaging across these studies gives the wrong impression that all studies have moderate power. Thus, p-curve estimates may be misinterpreted easily because p-curve ignores heterogeneity in true power.
Final Conclusion
In the datacolada 67 blog post, the Datacolada team tried to defend p-curve against evidence that p-curve fails when data are heterogeneous. It is understandable that authors are defensive about their methods. In this comment on the blog post, I tried to reveal flaws in Uri's arguments and to show that z-curve is indeed a better tool for the job. However, I am just as motivated to promote z-curve as the Datacolada team is to promote p-curve.
To address this problem of conflict of interest and motivated reasoning, it is time for third parties to weigh in. Neither method has been vetted by traditional peer-review because editors didn't see any merit in p-curve or z-curve, but these methods are already being used to make claims about replicability. It is time to make sure that they are used properly. So, please contribute to the discussion about p-curve and z-curve in the comments section. Even if you simply have a clarification question, please post it.


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redpajama_set_name: RedPajamaCommonCrawl


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English is the only prerequisite for entry into a single law degree, but there may be further requirements for double degrees.
You may also be able to apply for admission through a special entry scheme (mature age, course transfer, other entry for applicants failing to meet minimum tertiary requirements). This may require you to sit a special tertiary admission test.
Visit the VTAC website for all the information you need regarding requirements for application and terms of acceptance for all law courses at all tertiary institutions. Your VTAC guide will provide information on combined degrees, entry schemes and requirements, as well as guaranteed and fee places for each university.
Federal and State Constitutional Law.
What happens after completing tertiary study?
Once study requirements have been met, law graduates wishing to practise law begin their graduate training by undertaking either Practical Legal Training (PLT) or Supervised Legal Training (SLT) as an employee of a firm.
Following completion of either PLT or SLT, law graduates qualify to be admitted to practice providing they have met all of the admission requirements.
The completion of either Practical Legal Training or Supervised Legal Training is a requirement in order to be admitted to practice.
The Australasian Professional Legal Education Council (APLEC) and the Law Admissions Consultative Committee (LACC) have developed the revised Practical Legal Training Core Competencies for Entry-Level Lawyers (Core Competencies). These are also set out in Schedule 2 of the Legal Profession Uniform Admission Rules 2015 (the Rules).
The Core Competencies state that every applicant is required to satisfy the Victorian Legal Admissions Board that he or she has achieved the prescribed competencies in the "Skills, Compulsory and Optional Practice Areas and Values" (Required Competencies). Students are encouraged to familiarise themselves with the Core Competencies and the Rules.
Practical Legal Training (PLT) is the most commonly chosen pathway for admission to practise as a lawyer in Australia. Practical legal training is designed to ensure that graduates are fully prepared to enter the legal profession with the practical skills to complement their technical training.
Successful completion of a practical legal training program ensures the required Core Competencies are fully met.
Must be completed with an approved PLT provider.
Can be completed in under six months.
Consists mainly of course work (either online or on-site at the education facility), with a combination of practical work experience completed in a legal environment.
Is paid for by the student or the firm.
The College of Law (COL) is Australia's largest provider of Practical Legal Training and the only one with campuses in New South Wales, Victoria, Queensland and Western Australia.
Their programs are primarily delivered online via a Learning Portal developed specifically for online delivery, ensuring it is practical and relevant to the needs of a graduate lawyer. Graduates have access to a wide range of learning resources and the support of the college's lecturers. The online program is closely integrated with face-to-face activities giving graduates the best learning opportunities.
The Victorian office and lecturer rooms are located centrally in Melbourne's CBD.
Upon completion, graduates are awarded a Graduate Diploma in Legal Practice, qualifying them for admission to practice in Victoria. For more information please contact the COL Enrolments Office on 1300 865 111 or enrolments@collaw.edu.au or visit The College of Law Victoria website.
Leo Cussen Institute offers a PLT course that satisfies the practical legal training requirements for admission to the legal profession in Victoria and enables admission in other Australian states under mutual recognition rules.
The PTC is delivered in both onsite (face to face) and online programs. The online program includes substantial face-to-face contact. It is a 24-week course including 3 weeks professional placement. There are two intakes into each program each year (January and July).
On completion graduates receive a Graduate Diploma in Legal Practice and a Certificate of Satisfactory Completion qualifying them for admission to the legal profession in Victoria.
For further information contact Leo Cussen on ptcadmin@leocussen.vic.edu.au or visit the Leo Cussen Institute website.
ANU is Australia's leading University provider of Practical Legal Training (PLT). The ANU Graduate Diploma of Legal Practice (GDLP) provides not only the qualification you need to be admitted as a lawyer in Australia, the GDLP provides the skills you need to take the next step in your career in any professional environment. Designed to provide you with the practical skills and professional understanding you will need as a lawyer, the ANU GDLP builds on the knowledge you have gained in your Bachelor of Law degree or Juris Doctor, or equivalent.
The ANU GDLP program uses online learning to enable you to balance your PLT with employment, or other personal commitments and to study at ANU regardless of your location - our GDLP students are based all over Australia, and the world. Our initial 4 day face-to-face course (the only compulsory face-to-face component of the GDLP) is delivered all over Australia at various times throughout the year, including multiple offerings in Victoria.
Supervised Legal Training (SLT) is a 12-month traineeship with a legal firm or office, working under the supervision of a practitioner.
Graduates completing their traineeship with a firm are referred to as law graduates or legal trainees.
Predominantly practical training as an employee of a firm.
Mandatory requirement to complete ten core competencies.
Some compulsory external training is required.
Throughout the traineeship year, a law graduate must complete training in the Core Competencies for Entry-Level Lawyers (Core Competencies), which are also set out in Schedule 2 of the Legal Profession Uniform Admission Rules 2015 (Rules).
Following the completion of SLT individuals and firms need to comply with the admission requirements under the Rules including providing particular information to the Victorian Legal Admissions Board.
During the 12-month traineeship, law graduates must acquire appropriate understanding and competence in each of the Required Competences including the compulsory "skills", "practice areas" and "values". Trainees are also expected to complete training in two optional practice areas chosen in consultation with their employer.
The majority of the training required can be completed either in-house (on the job), externally with an accredited practical legal training (PLT) provider, or through a combination of both.
Where a trainee has completed training through an external training provider, a document certifying the trainee's satisfactory completion of the training module should be retained.
Ethics and Professional Responsibility, Lawyer's Skills and the Risk Management element of Work Management and Business Skills must be completed through a PLT provider, or another provider approved by the Victorian Legal Admissions Board (see Schedule 3, Clause 6(1)(c) of the Rules).
For more information on seeking approval to teach these areas within a law firm or organisation please visit the Victorian Legal Admissions Board website.
Jessica is working at a medium sized boutique firm; she is able to complete all the skills, practice areas and values through file work under the supervision of different partners of the firm. As required under the rules, Jessica is enrolling to complete Ethics and Professional Responsibility through a PLT provider and is seeking approval from the Victorian Legal Admissions Board to cover Lawyers Skills and Risk Management internally with the firm.
Michael is completing his traineeship with a specialist Criminal Law firm. Michael is enrolling to complete Ethics and Professional Responsibility through a PLT provider and is seeking approval from the Victorian Legal Admissions Board to cover Lawyers Skills and Risk Management internally. Michael will also need to complete his training for the compulsory practice area(s) through a PLT provider as he cannot complete them internally.
any other relevant information that the Board may require.
Law graduates from regional Victoria are encouraged to call the Victorian Legal Admissions Board and request approval to submit their documents by post.
Law graduates must also arrange for their university to send directly to the Victorian Legal Admissions Board an original academic transcript, setting out the results obtained, as evidence they have satisfied the academic qualifications referred to at rule 5(1) of the Rules.
The Training Plan acts as a 12-month timetable outlining the competency standards the law graduate will cover during their traineeship year and must be approved by the Victorian Legal Admissions Board.
Where the Training Plan is not approved by the Victorian Legal Admissions Board it may give the law graduate leave to withdraw and to resubmit the training plan within a specified period so that any necessary amendments can be incorporated.
Once this new Training Plan is approved any period of training that has been undertaken prior to the Victorian Legal Admission Board's approval will be taken to be training and therefore be included towards the required 12 months of training.
A workbook must be maintained throughout the traineeship, which records the law graduate's completion of each task and demonstrates competence in each element of the skills, values and practice areas.
For up-to-date information for law graduates and firms, please visit the Supervised Legal Training section of the Victorian Legal Admissions Board website or contact the Victorian Legal Admissions Board on 03 9604 2451 or vlab@justice.vic.gov.au. The Victorian Legal Admissions Board has also produced a Guide for Supervised Legal Training.
The Legal Profession Uniform Admission Rules 2015 (Rules) came into effect on 1 July 2015 and replaces the Legal Profession (Admission) Rules 2008. Law graduates are encouraged to read the Rules carefully to familiarise themselves with the admission requirements and the documents required to be submitted to the Victorian Legal Admissions Board.
An academic transcript from the law graduate's university as evidence of qualifications, and a certificate of completion of a PLT course (if one has been completed) – to be sent directly to the Board by the educational institution (see rule 15 of the Rules).
An original Student Conduct Report from the law graduate's university and PLT provider – to be sent directly to the Board by the educational institution (see rule 19 of the Rules).
A National Police Certificate (see rule 18 of the Rules).
Two character statements (see rule 16 of the Rules).
A disclosure statement statutory declaration if required (see rule 17 of the Rules).
A capacity disclosure statutory declaration if required (see rule 17 of the Rules).
Photo identification must also be shown.
All law graduates are strongly encouraged to read the Guide for Applicants – Admission as a Lawyer in Victoria before completing the Application for Compliance Certificate.
These can be found on the Victorian Legal Admissions Board website.
All law graduates must lodge an original typed Application for Compliance Certificate, which must be filed in person. Correct photo ID must be shown. If the ID does not show a date of birth or an address then a secondary form of ID such as a utility bill must be shown.
For law graduates who reside 100kms from the Melbourne CBD, applications will be accept by post with a certified copy of their ID.
The Victorian Legal Admissions Board is located on the Ground Floor at 451 Little Bourke Street, Melbourne.
Please visit the Victorian Legal Admissions Board website for further information on admission requirements.
What is the difference between Practical Legal Training (PLT) and Supervised Legal Training (SLT)?
Since July 2008, there have been two paths to admission for law graduates in Victoria – Practical Legal Training (PLT) or Supervised Legal Training (Traineeships).
PLT comprises a combination of formal coursework and a period of work experience and is available from providers such as The College of Law, Leo Cussens Centre for Law, and Australia National University (ANU) College of Law.
A Traineeship involves 12 months of supervised workplace training in a law firm and some additional compulsory training with an external provider.
What do most Victorian law graduates do for training?
Most law graduates do a PLT program. This is the case across Australia and in some states there is no traineeship alternative.
What is involved in PLT?
A PLT program consists of a combination of coursework and work experience.
PLT coursework and Traineeships must both cover the National Competency Standards prescribed by the Australasian Professional Legal Education Council (APLEC), the Law Admissions Consultative Committee (LACC) and all the admitting authorities in Australia.
What subjects do I have to do in PLT?
Is there any choice of subjects with PLT?
Can I study PLT online?
Yes. Each of the PLT providers in Victoria offer online courses. However there is often some compulsory face to face teaching blocks. Check with each of the providers as to their courses' specific requirements and structure.
How long will PLT take?
You can study full-time in which case the PLT coursework component will take 15 weeks; part-time will take you 30 weeks. You also need to do your work experience which can be concurrent with the part-time option.
Taking into account the work experience requirement, you can be ready for Admission in only 30 weeks compared to the 52 weeks required by SLT.
You'll need to allow 30 to 35 hours of study a week for the full-time program and about 15 to 17 hours a week for the part-time program.
When can I start PLT?
and the applicant has received the prior permission of the Board to commence the PLT course.
The College of Law runs a number of PLT programs through the year. Generally you will be able to start in December, January, March, April, May, July or October.
The Leo Cussen Centre for Law runs PLT programs beginning in January and July.
Click here for information on starting dates for Australian National University (ANU).
How much does PLT cost?
Check The College of Law website, Leo Cussen Centre for Law website, and Australian National University (ANU) website for the current fees.
You can pay by using FEE-HELP which is a loan available via the Higher Education Loan Program or you or a law firm can pay upfront.
How much work experience do I need?
With The College of Law you need to undertake 75 days of work experience, some of which can have been done during your law degree. An alternative option is to do the Clinical Experience Module which involves 25 days of work experience and additional coursework that accounts for 50 days of work experience.
With Leo Cussen Centre for Law you need to undertake a three-week professional placement. In the Onsite PTC, the professional placement takes place after you have completed the formal PTC work and is arranged by the institute. In the Online PTC, you must arrange the placement and it must be approved by the Director PTC.
For information about work experience during the Australian National University (ANU) PLT course, see the ANU website.
The rules about Work Experience differ from state to state.
How do I obtain work experience?
You can find positions in a variety of ways, for example by checking your university careers centre, The College of Law Career Centreor the LIV Graduate Employment Registry or by asking around at the careers fairs.
How do I enrol in PLT?
You can apply to enrol online at The College of Law, Leo Cussen Institute, or Australian National University (ANU), or send in a paper application.
You will need your FEE-HELP application or payment details to finalise your application.
We will also need a certified copy of your Academic Transcript when it is available and before you complete your PLT coursework.
Are there quotas or waiting lists?
PLT programs do not have quotas or waiting lists but does ask you to enrol at least two weeks prior to the start date of your program of choice. However, first preference may be given to applicants who meet the prerequisites at the time of application.
Can I commence PLT while completing Academic Qualifications?
According to the revised Core Competencies, an applicant may now commence PLT whilst still completing their academic qualifications, providing they have no more than two subjects to complete. However, the outstanding two subjects cannot be Priestly 11 subjects, they must be two elective subjects. Prior permission must be granted by the Victorian Legal Admissions Board to allow a student to commence the PLT whilst still completing their academic qualification.
For further information, visit the Victorian Legal Admissions Board website.
Will the Legal Profession Uniform Admission Rules 2015 affect me?
If you are intending to seek admission to practice in the future, then yes the Rules will affect you.
meet the costs of the trainee's supervision and training.
who has worked as either or both a practising solicitor or practising barrister for a minimum total of five years (of which at least the three years before the person commences to supervise a trainee were spent in either or both of practice as a solicitor, or working in the manner of a solicitor).
What is the applications deadline for traineeship positions?
The LIV Traineeship Guidelines stipulate the key recruitment dates for firms who are signatories to the Guidelines.
referring to the Careers Guides published by the law students' societies at each of the Victorian law schools.
These publications generally contain contact details, important dates, areas of practice and other information about traineeships and seasonal clerkship opportunities specific to each law firm.
Is there an alternative to SLT?
You can also gain admission to practice in Victoria by completing a Practical Legal Training course.
How many trainees can a supervisor engage?
Under Schedule 2, Clause 5(3), a person must not be the supervisor of more than one trainee at the same time without prior approval from the Victorian Legal Admissions Board. The Board have produced guidelines for supervisors wishing to supervise more than one trainee. View the guidelines.
What is the duration of the traineeship?
Traineeships are for 12 months but it is also possible for traineeships to be completed part-time over a two-year period. If you wish to undertake part-time supervised legal training over a period of 24 months you should contact the Board on 03 9604 2451. A formal application must be made to the Board prior to commencement of your traineeship.
What do I need to do when I start my SLT (traineeship)?
If you are an applicant from regional Victoria you are encouraged to call the board and request approval to submit your documents by post.
You must also arrange for your university to send directly to the Board an original academic transcript, setting out the results obtained, as evidence you have satisfied the academic qualifications referred to at Rule 5(1).
For further information visit the Law Admissions website.
When can I start and finish my traineeship?
The traineeship must be 12 months duration. Provided the trainee has completed all the requirements of the LLB there are no restrictions or guidelines for when a traineeship must commence. Therefore the commencement date may be negotiated between the trainee and the firm.
I have completed my law degree but have not graduated, can I commence my SLT or PLT?
Yes. Provided you have satisfies the requirements of the LLB you may commence your traineeship. You must however have formally graduated before you are admitted to practice or apply to the Board for admission prior to graduation.
How do I know what work I need to do to comply with the competency standards?
Schedule 2 of the rules lists the elements for each competency standard as well as the performance criteria that should be met in order to satisfactorily comply with the rules.
Do employers need to keep formal records of the training provided?
It would be prudent for employers to keep a record of any formal training conducted externally or specifically referred to in the training plan (similar to the records which might be kept in order to comply with the Continuing Professional Development Rules). Trainees are also encouraged to keep a diary of the work they are completing which complies with the performance criteria listed in schedule two.
During the Supervised Legal Training who should pay for the cost of any external training?
a trainee meeting the requirements of rule 6 (1).
Who can conduct the required training?
Trainees may complete the majority of their training either in-house with their workplace or externally with an accredited Practical Legal Training provider or through a mixture of both.
Ethics and Professional Responsibility, Lawyer's Skills and the Risk Management element of Work Management and Business Skills must be completed through a PLT provider, or another provider approved by the Victorian Legal Admissions Board (see Schedule 3, Clause 6(1)(c).
All other areas of competency may potentially be conducted in-house by the employer.
I have decided to study a different elective; do I need to re-lodge my training plan with the Board of Examiners?
Any minor alterations to your training plan should be set out in Schedule 6 (Employers – Completion of Supervised Legal Training) at the conclusion of your traineeship. Any major alterations should be discussed with the Board on 03 9604 2451.
Can we get approval to teach a different optional area to the ones listed in the Rules?
Trainees must complete one optional practice area from the identified practice areas and an employer who wishes to provide training in an alternative practice area must apply by statutory declaration for the Board's approval (Schedule 12).
The statutory declaration should be lodged with the Board before the training plan. Once an employer has been approved to provide training in an alternative optional practice area that approval will be ongoing, provided that the employer exhibits a copy of the approved application to the training plan of any future supervised legal trainees.
In circumstances where the Board has granted approval to provide a course of instruction in an Alternative Optional Practice Area each new trainee must file a statutory declaration seeking dispensation in accordance with the Rules to include an alternative optional practice area (Schedule 13).
How many annual leave days is a trainee entitled to?
a further period not exceeding 20 days.
If a trainee takes a leave of absence for any period in addition to these periods, the trainee must complete an equivalent additional period of Supervised Legal Training.
Can a trainee engage in additional paid or unpaid work during the Supervised Legal Training?
in accordance with the relevant training plan.
Who pays for admission fees?
It is the responsibility of the applicant to pay the admission fees. An employer may agree to pay your admission fee but it is not a requirement of the Admission Rules.
I have a law degree from interstate. How do I commence a traineeship in Victoria?
In exactly the same manner as a Victorian law graduate.
Will my law degree still be valid if I don't do my traineeship immediately after my degree?
Can a law graduate's SLT ever be terminated?
for any other reason it is appropriate to do so.
approve another appropriate employer and one or more eligible supervisors to provide the balance of the training, under a revised training plan.


We have a new Junior Champion of Cyprus! Very happy and proud of our Russian boys!
Autumn National Dog Show, 05/10/2018, Limassol, Cyprus.
Le Nain Adorable Joie (junior class) got CW, EXC-1ST, CAJC, BJOB, BOB !!!
Le Nain Adorable Zeppelin (baby class) got CW, VP-1ST, BEST BABY OF BREED AND 3RD BEST BABY IN SHOW!!!
Le Nain Adorable Joie (junior class) got CW, EXC-1ST, CAJC, BOS !!!
Breeders:Olga Nikolaeva Anastasia Nikolaeva Thank you dear Olga and Anastasia for these wonderful boys!!!
CW, CAC, CACIB, BOS, Best female!
Many thanks to the judges who recognised the quality of our little princess!


text:
Israel Commentary
Neglected information and opinion relative to Israel, the Middle East and the immediate world.
Tag: Defense cuts
Retiring Sec. of Defense, Robert Gates, 'Wake up Obama. Your cuts in our defense budget are killing us'
The title above, a paraphrase, of course (jsk)
'Enough'
The Weekly Standard, JUN 6, 2011, VOL. 16, NO. 36
BY GARY SCHMITT AND THOMAS DONNELLY
In the next month, after more than four decades of distinguished public service including almost five extraordinary years at the Pentagon supervising the successful surges in Iraq and Afghanistan, Defense Secretary Robert Gates will retire. He departs as the very model of a Washington "wise man," having served in senior positions in two Democratic and three Republican administrations—the best the inside-the-Beltway establishment has to offer. His parting words, delivered in a series of valedictory speeches, carry the weight of his long experience and sober judgment.
Gates's career spans a remarkable period from the Cold War to today, the events of which raised immense hopes—none more than the collapse of the Soviet Empire—and were punctuated by deep darkness—9/11 and the year 2006 in Iraq.
In his May 22 speech at the University of Notre Dame commencement, Gates summed up the classical wisdom of a conservative: "If history—and religion—teach us anything, it is that there will always be evil in the world, people bent on aggression, oppression, satisfying their greed for wealth and power and territory, or determined to impose an ideology based on the subjugation of others and the denial of liberty to men and women."
If mankind has fallen, the United States of America still struggles to lift it up. "Since I entered government 45 years ago, I've shifted my views and changed my mind on a good many things as circumstances, new information, or logic dictated," Gates allowed in a speech last week at the American Enterprise Institute that developed the themes of his commencement address. "But I have yet to see evidence that would dissuade me from this fundamental belief: that America does have a special position and set of responsibilities on this planet."
To protect and promulgate its liberties and the cause of liberty, America must be strong. "More than any other secretary of defense, I have been a strong advocate of 'soft' power—of the critical importance of diplomacy and development as fundamental components of our foreign policy and national security." But, said Gates, "Make no mistake: the ultimate guarantee against the success of aggressors, dictators, and terrorists in the 21st century, as in the 20th, is 'hard' power—the size, strength, and global reach of the United States military."
This is the heart of the matter. During his service under Barack Obama, Gates has been directed to make three significant rounds of reductions in Pentagon plans and budgets. The first came in early 2009. As the Obama administration prepared to inject $800 billion in "stimulus" into the faltering U.S. economy, canvassing agencies for "shovel-ready" projects, it ordered weapons cuts that totaled about $330 billion.
In 2010, seeing the shifts in the domestic political landscape, Secretary Gates seized the initiative to wring $100 billion in "efficiencies" from defense programs, hoping he would be permitted to reinvest the money in higher priority procurements. He got to keep about three-quarters of the "savings," but the White House took not only the remainder but another $75 billion.
The net result was that Gates transferred $78 billion from one Pentagon pot to another, but a further $100 billion was cut. The third round began on April 13, when the president announced—though he hadn't informed Gates until the night before—that the Defense Department would contribute another $400 billion to his "deficit reduction plan."
If brought to fruition, the Obama administration will have sliced something on the order of 15 to 20 percent out of the already overstretched military it inherited. The dollar figures don't reflect the full extent of the damage, but the loss in power is clear: The Army and Marine Corps will return to their pre-9/11 size, and major land, sea, and air projects have been reduced, ended early, or never brought into production. And it might be worse: Secretary Gates has acidly described the defense cuts called for by the chairmen of the president's deficit commission, Alan Simpson and Erskine Bowles, as "catastrophic," driven by budget "math, not [military] strategy."
Gates's parting wisdom can be boiled down to one word: enough. The "low-hanging fruit," he declared at AEI, "those weapons and other programs considered most questionable, have not only been plucked, they have been stomped on and crushed." The fat has been trimmed; what's left is bone.
Gates also defined the challenge for the man nominated to be his successor, Leon Panetta, who's been a strong director of central intelligence but who also, as a congressman in the 1990s, led the charge to reduce defense spending. "We need to be honest with the president, with the Congress, with the American people, indeed with ourselves, about what the consequences [of further defense cuts] are: that a smaller military, no matter how superb, will be able to go fewer places and be able to do fewer things."
Gates's warning should be a call to arms for conservatives who, in election after election, have retained the public's trust by adhering to the principle that American military preeminence is absolutely essential if we want security at home and great-power peace abroad.
It is a platform that Republicans in Congress and those running for president, in particular, need to reaffirm. Former Minnesota governor and 2012 presidential candidate Tim Pawlenty got it precisely right when he said: "I'm not one who's going to stand before you and say we need to cut the defense budget. . . . I'm not for shrinking America's presence in the world. I'm for making sure America remains the world leader."
Through the surges in Iraq and Afghanistan, Bob Gates has seen the thin line that separates "too few" from "just enough." He knows how hard it is to turn defeat into a chance for victory. When he says "enough," conservatives—and all Americans—should listen.
Author Jerome S. KaufmanPosted on June 13, 2011 June 13, 2011 Categories UncategorizedTags Defense cuts, Hard vs. Soft power, Leon Panetta, Tim Pawlenty, Victory into Defeat
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Welcome, to the Studio! I'm excited to be participating in a fun blog hop today...needless to say I'm "out and about" hopping, too!
The range of papers by DCWV were textural heaven and a lovely match for my Faber-Castell Design Memory Craft mediums!
I stamped my image (Penny Black 40-276 Botanical Notes) onto the DCWV Adhesive Fabric Paper using a Black Stamper's Big Brush Pen. Next I colored in my image using Art GRIP® Aquarelle Watercolor Pencils. I added a generous amount of water to blend, allowing some of the color to bleed onto the background areas of the image.
To intensify the color even more, while the fabric paper was still wet, I mix and matched my mediums and added in some color using Stamper's Big Brush Pens. Finally, I removed the adhesive backing sheet and placed the fabric onto a piece of white cardstock, adding in a few wrinkles for extra texture. I layered this piece onto a piece of paper from the DCWV Corrugate Neutral Stack. Finally, I layered this onto a piece of white DCWV Woven Paper and a white notecard.
There are some great prizes along this hop, too, my friends! Faber-Castell Design Memory Craft and DCWV will be giving away $75 in product at the end of the hop. To win, follow the list below and leave a comment. The hop will end at 5PM EST on Friday, March 28th. The winner will be announced on Monday, March 31st on each of the company's blogs. For extra entries, follow Faber-Castell Design Memory Craft and DCWV on twitter!
This is so very beautiful, Jill!
This is beautiful! You're coloring is wonderful and I love the composition of the card! Great job!
This is gorgeous!!!!! stunning really! TFS!
Very pretty with your vivid colors!
this is stunning! the image looks amazing on the fabric paper, thanks for the great inspiration!
Gorgeous. Love the bit of corrugated texture peeking through.
Fabulous project! So fun...LOVE the bright flowers.
This is simply the best! Pinning your amazing project, love the watercolours and the fact that despite being water-colours they are still bold and intense in places. Love it all!
Love the colors and how they bleed into the background...this is truly a stunner!
Jill, what a beautiful, beautiful, project. Those stamps along with the watercolor pencils is fantastic!! Love the layering of the texture papers too.
Beautifully colored. The layers are yummy.
Beautiful. The flowers burst off the page. The blue butterfly is so pretty. Love the shabby look of the papers and the use of the corrugated paper. Great job.
Oooooh - I love your project! So colourful and tactile!
Beautiful and bright. Love the flowers and the butterfly. The effect you achieved with the watercolour is really eye catching.
WOW! This notecard is stunning! I love all the blended colors and how the bled into the background fabric piece. I also love how you put in a corrugated piece! It really looks wonderful!
Wow... This is Gorgeous. I love the color, It is beautiful. And the texture.... Oh I can go on and on. Wonderful job.
Jill, this card is just stunning! And lucky me, I have the stamp!! Yay! I haven't used it yet but I'm going to : ) Thanks for the colorful and wonderful inspiration.
Love the project. Always loved your color combos.
Beautiful!! Very elegant card!! Love the colors!
I am always awed by your talent! Thanks for sharing.
Jill, your talent and creativity is really second to none. This is absoutely GORGEOUS. Thanks so much for sharing and inspiring us with your beautiful work!!
Very beautiful! You are so talented!
Your stamp and colors love so, so pretty on the fabric paper. I love this!
Oh wow! What a way to end the hop! Stunning! The vividness of the color and the coloring are breathtaking!
Wow, I just spent 20 minutes trying to get this comment form to show up. Just wanted to let you know that your project is gorgeous. The cloth adhesive paper looks like it would be very cool to use.
I really like the way the colors came out. It all goes well together.
Love the colors! Very pretty! TFS!
Wow! This is stunning. Love the color and texture.
Gorgeous! So pretty! I love the colors and the layering of textures.
Amazing project with such beautiful stamping and great colorwork. It came out so beautiful and so much fun. Great job.
Beautifully done as always girlie!
SO MUCH to LOVE Jill!!! LOVE the image, LOVE the colours, LOVE how you let the colours bleed to add a magic glow in the background, LOVE the textures, LOVE how you have added wrinkles and peeled off the corner to reveal the corrugates too => LOVE IT ALL!!!
This is very beautiful! Very bright and lively!! Thank you for sharing.
Such a beautiful look with the water coloring of those FC pencils! Great card...textures are felt!
So pretty - love the watercolor look and corrugated paper.
Beautiful. Love how you bled the colors.
I love all your stuff. This is so beautiful. Thanks for sharing.
Jill, I really love this! So fresh and springy looking! Thank you for sharing this inspiration with us!
Beautiful work! This is a project I feel like I can tackle. Thanks so much for the inspiration!
Now that is some spectacular color. I really like this corrugated texture. Awesome project! thanks for sharing with us!
This is so beautiful! Love how bright the colors turned out.
i love this, so simple, and so beautiful!
This is wonderful. Thanks so much for sharing your marvelous talent.
Wow, it is great. Your butterfly is beautiful.
Stunning! I love the vibrant colors and the butterfly, thanks for sharing.
Yowzah!!! This is the most beautiful project on the hop, in my humble opinion. One of my favorite stamps on a shabby chic looking card, it is to die for. Thank you for sharing your talent with us.
Absolutely breathtaking! Beautiful use of color. Two thumbs up for this project!
Beautiful work chickie! Your creations always catch my eye!
As always, your project is amazing. Thanks for sharing.
Beautiful work. thanks 4 sharing.
That is AMAZING!!!! Love the gorgeous color and the layers you used!!
Love how you let the colors bleed outside the lines. And the cardboard add a beautiful texture.
I have to try this technique! I love the bright, vibrant colors! Thanks for the wonderful tips!
I like how you let the color bleed.
Wow this is beautiful work! Great job. I would love to come back and visit here. Great inspiration everywhere.
How exquisite! Your project takes my breath away. I love the colors you used and how you layered them. Thank you so much for sharing.
Lovely project. The colors you chose caught my eye immediately. Thank you for sharing this piece of inspiration.
What beautiful, vibrant colors! Nicely done.
This adhesive fabric paper looks awesome, that is what I want to get my hands on! Also love the cork and burlap! Your card turned out beautifully! And I loved seeing how everyone was using the different faber-castell products too. Thanks for sharing.
I love this page. Awesome work!!
Stunning card. Thank you for sharing.
Love the colors, it's beautiful.
Gorgeous project as always!! I've followed for a long time and really enjoy your projects and tutorials!
Jill this is absolutey gorgeous. Love all the colors, Thanks so much for sharing all your creativity to all of us out here in blog land.
Holy moly, this is gorgeous!!!! Love it!
I LOVE how you colored this stamp!! And the colors and textures are just gorgeous!
Love the textures, colors, thanks for the inspiration.


Funda recently gave its website a new look and feel. With almost 30 million visits and 390 million page views a month Funda is one of the most popular websites in The Netherlands. De Voorhoede was responsible for building a completely responsive front-end. Our challenge was to ensure individual product teams could work seamlessly on the same front-end.
When it's always clear what's being done by each team, you prevent them doing the same thing twice. Transparency also allows you to review and improve each other's work.
All developers use the same vocabulary for all parts of the website. Designers, back-end developers and other stakeholders understand and use this terminology as well. The same goes for coding conventions (guidelines on how to write your code).
All teams should be able to work and make progress independently of each other. This also applies to all disciplines within a team.
Each team is responsible for a different part of the website. For example, a search field is used in many places within the site. Each team should be able to find and use the code for this search field easily. Reusing components provides consistency for end users and speeds up development.
Our front-end guide is a custom made component library.
We always develop and test components in isolation. This way we make sure that subsequent changes will not affect the rest of the website. When a component is delivered but not ready to use, you can implement it at a later stage without any hassle.
A front-end guide provides an overview of all components and pages. Everyone has access, including product owners, designers and back-end developers. Components are carefully documented and combined with an live example usages. This helps with a smooth handover between developers. Another benefit is that the client and stakeholders always have access to the latest version of the front-end. Especially useful for feedback and demos.


As part of ILO's project with the Small and Micro Enterprise Promotion Service (SMEPS) to improve Yemeni youth's accessto Decent Work, the Mubadara Entrepreneurship Education programme was developed and pilot tested in eight Yemeni universities targeting youth in their graduating year. As part of the programme, a business plan competition is planned to be held in partnership with the private sector and the sponsorship of Al Tadhamon and Al Kuraimi Banks. The winners of the competition will receive financial and/or in-kind support for the establishment of their business start-up.
As part of the programme, a Training of Coaches (TOC) workshop was held in Al Bustan Hotel in Sana'a between November 28 and December 5, 2014. The workshop targeted 26 professors and private sector employees from different areas of Yemen; these men and women will be coaching the 50 graduates whose business plans are selected for entry in the business plan competition. The participants were enthusiastic to learn coaching skills and support Yemeni youth in developing their business plans.
Approximately 380 plans were submitted by students after taking the Mubadara course, showing their great interest in establishing their own business in the future. In 2014, the Mubadara programme reached a total of 1,044 students in 8 universities with 24 teachers instructing across 5 governorates of Yemen.
During the training of coaches' workshop, a number of prominent Yemenis showed their support for fostering entrepreneurial attitudes among Yemeni youth and the need for close involvement of the private sector to facilitate the process and coach these young people. The opening ceremony speakers included Mr. Youssef Kuraimi, Head of Al Kuraimi Bank, Mr. Rifaat El Miamary, Deputy of the Executive Director at Al Tadhamon Bank, Dr. Ali Qassem, Deputy Minister in the Ministry of Higher Education and Scientific Research, and Mr. Ibrahim Al Hugari, former Minister of Technical Education and Vocational Training.
In addition, the Minister of Higher Education and Scientific Research Mr. Mohammad Motahar and Mr. Al Nashmy, Dean of the Faculty of Public Administration from the University of Sciences and Technology, attended the workshop's closing ceremony and distributed certificates of attendance to the participants. The Minister expressed his support of the Mubadara programme and expressed the need to establish entrepreneurship centers in Yemeni universities.
Currently, a revision of the business plans is underway and the top 50 applicants will be contacted in the coming weeks to confirm their enrolment in the Business Plan Competition and move forward in further developing their plans with their assigned coaches.


Most Redoing Home Electrical Wiring Collections - Conversations with pinnacle electricians have provided us with a a list of steps to take so that you can make rewiring continue extra smoothly, with fewer holes punched inside the walls, floors, and ceilings—or, heaven forbid, a structural beam. Growing a easy cut thru a hollow noticed or careful paintings (backside) will make it simpler to make partitions or ceilings whole again. Uneven access holes, like this one punched in the author's house (top), prove tough to patch. (Images: tony seideman/peter method).
The needs of modern generation can exacerbate the scenario, and that they're vulnerable to doing so all the time. Older homes have been constructed at a time when 60 amps was considered lots of energy for a single residence. By way of assessment, maximum new homes are constructed with one hundred fifty- or 200-amp carrier, however one hundred amps changed into the same old for decades—and most professionals agree that anything much less than one hundred amps is unlikely to satisfy the electrical wishes of a present day household. New wiring structures often can be run near the vintage—as on this vintage house that's been effectively rewired, with a brand new field positioned near now-defunct ceramic knobs at the basement ceiling. (Photograph: peter method).
1. Do an "electric stock," creating a list of all of the gadgets you'll be using inside the house, and where. Your electric machine needs to in shape your desires; identifying in which and the way you'll be the use of strength makes it less difficult to frame the parameters of the task. Computer systems, blenders, tvs, even fridges—none of those existed whilst many historical houses have been constructed and first stressed out. So upgrading electric structures is an vital undertaking for numerous old homes. But efforts to replace electric structures can often result in harm to historical homes. One in all the largest errors many restorers make is to try to update every piece of old wiring in the gadget, says michael hedrick of historical electric powered protection in fredericksburg, virginia. ??most efforts tend to be heavy-handed and replace extra than what is simply important to an older machine. Many parts of an older wiring machine, if they had been undisturbed, are nevertheless pretty usable and moderately safe," he says. ??bottom line, after inspection by means of a competent and qualified electrician, leave plenty of what you locate in area and working. There are many homes with electric structures from the 1920s nonetheless turning in electricity in a safe and efficient manner.??.