Em Qua, 2008-08-13 às 19:14 -0700, Mark Home escreveu: > Dear All: > > I have a clinical study where I would like to compare the demographic > information for 2 samples in a study. The demographics include both > categorical and continuous variables. I would like to be able to say whether > the demographics are significantly different or not. > > The majority of papers that I have read use multiple techniques to achieve > this (e.g., t-test for the continuous variables and either Fischer exact or > Chi-square for categorical). I wonder whether this might lead to spurious > differences due to multiple significance tests. Is there a better way to do > this? > > Thanks in advance for your advice, > > Mark
Mark, You need make multiple comparison correction. The most know correction is Bonferroni. In this case you make new p value = alpha/n where alpha is "alpha" of planning your study and "n" is a number of test you using. Example If may clinical study have a alpha = 0.05 and i make 10 test my ne p-value is 0.05/10 = 0.005 -- []s Tura ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
