I still need to do some repetitive statistical analysis on some outcomes from a dataset.
Take the following as an example; id sex hiv age famsize bmi resprate 1 M Pos 23 2 16 15 2 F Neg 24 5 18 14 3 F Pos 56 14 23 24 4 F Pos 67 3 33 31 5 M Neg 34 2 21 23 I want to know if there are statistically detectable differences in all of the continuous variables in my data set when subdivided by sex or hiv status (ie are age, family size, bmi and resprate different in my male and female patients or in hiv pos/neg patients) Of course I can use wilcoxon or t-tests e.g: wilcox.test( age~sex) wilcox.test(famsize~sex) wilcox.test(bmi~sex) wilcox.test(resprate~sex) wilcox.test( age~hiv) wilcox.test(famsize~hiv) wilcox.test(bmi~hiv) wilcox.test(resprate~hiv) but there must be some easy way of looping/automating this code (i.e. get all the continuous variables analysed one by one by sex, then analysed one by one by hiv status). Obviously my actual dataset is considerably bigger than what is shown here - I have many variables to assess making the longhand instruction to do every test pretty unsatisfactory. I think I can use ‘for’ or some other looping command for this purpose but I can’t work out how. I think I don’t properly understand how loops work yet as I'm still quite new to R. Please could someone help – ideally with an explanation and some quick sample code? Derek -- View this message in context: http://r.789695.n4.nabble.com/Using-functions-loops-for-repetitive-commands-tp3498006p3498006.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
