Comparing p-values for samples of different size is a common mistake. Researcher 2 from Example A does everything as Example B: described above, but for convenience, his patients are all from the student health center of the prestigious university where he works. He claim that his result applies to patients other than cannot those of the age and socio-economic background, etc. of the ones he used in the study, because his sample was taken from a smaller population. Researcher 2 proceeds as in Example A, with a sample Example C: carefully selected from the population to which he wishes to apply his results, of an outcome but he is testing for equality of the means variable for the two groups. The hypothesis test he uses requires that the variance of the outcome variable for each group compared is the same.
Comparing p-values for samples of different size is a common mistake. Example B: Researcher 2 from Example A does everything as described above, but for convenience, his patients are all from the student health center of the prestigious university where he works. He cannot claim that his result applies to patients other than those of the age and socio-economic background, etc. of the ones he used in the study, because his sample was taken from a smaller population. Example C: Researcher 2 proceeds as in Example A, with a sample carefully selected from the population to which he wishes to apply his results, but he is testing for equality of the means of an outcome variable for the two groups. The hypothesis test he uses requires that the variance of the outcome variable for each group compared is the same.
WorkshopSlidesDayTwo2017-part3.docx