Using functions/loops for repetitive commands

Hello, Derek,

see below.

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)
.... [snip]

Define, e. g.,

my.wilcox.tests <- function( var.names, groupvar.name, data) {
  lapply( var.names,
          function( v) {
           form <- as.formula( paste( v, "~", groupvar.name))
           wilcox.test( form, data = data)
           } )
  }


and call something like

my.wilcox.test( <character vector with relevant variable names>,
                 <character string with relevant grouping variable>,
                 data = <your data set as data frame>)

Caveat: untested!

  Hth  --  Gerrit

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