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 [[alternative HTML version deleted]]
Use a smaller alpha value rather than 0.05. C On Thu, Aug 14, 2008 at 10:14 AM, Mark Home <rhelpadd at sbcglobal.net> wrote:> 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 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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. >-- CH Chan Research Assistant - KWH http://www.macgrass.com
Bernardo Rangel Tura
2008-Aug-14 09:41 UTC
[R] Comparison of demographics between 2 study samples
Em Qua, 2008-08-13 ?s 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, > > MarkMark, 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
On Wed, 2008-08-13 at 19:14 -0700, Mark Home wrote:> 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? >Hi Mark, Most of these comparisons are uncorrected, as the aim is to demonstrate that the samples come from the same population. Therefore, you aren't worried about making a Type I error, but ignoring a sampling difference that might bias your results. Jim