title: Generating/plotting a log-normal survival function
body: <p>I have an accelerated failure time model in SAS LIFEREG that I'd like to plot. Because SAS is to profoundly bad at graphing, I'd like to actually re-generate the data for the curves in R and plot them there. SAS puts out a scale (in the case of the exponential distribution fixed to 1), an intercept, and a regression coefficient for being in the exposed or unexposed population.</p>
  
  <p>There's two curves, one for the exposed and one for the unexposed population. One of the models is an exponential distribution, and I've produced the data and graph like so:</p>
  
  <pre><code>intercept &lt;- 5.00
  effect&lt;- -0.500
  data&lt;- data.frame(time=seq(0:180)-1)
  data$s_unexposed &lt;- apply(data,1,function(row) exp(-(exp(-intercept))*row[1]))
  data$s_exposed &lt;- apply(data,1,function(row) exp(-(exp(-(intercept+effect))*row[1])))
  
  plot(data$time,data$s_unexposed, type="l", ylim=c(0,1) ,xaxt='n',
       xlab="Days since Infection", ylab="Percent Surviving", lwd=2)
  axis(1, at=c(0, 20, 40, 60, 80, 100, 120, 140, 160, 180))
  lines(data$time,data$s_exposed, col="red",lwd=2)
  legend("topright", c("ICU Patients", "Non-ICU Patients"), lwd=2, col=c("red","black") )
  </code></pre>
  
  <p>Which gives me this:</p>
  
  <p><img src="https://i.stack.imgur.com/IDgHg.png" alt="enter image description here"></p>
  
  <p>Not the prettiest graph ever, but I don't really know my way around ggplot2 enough to spruce it up. But more importantly, I have a second set of data that comes from a Log Normal distribution, rather than an exponential, and my attempts to generate the data for that have failed utterly - the incorporation of the cdf for the normal distribution and the like puts it beyond my R skills. </p>
  
  <p>Anyone able to point me in the right direction, using the same numbers, and a scale parameter of 1?</p>