[R] How to apply two parameter function in data frame

[David L Carlson]

Try this.

> set.seed(123)
> a <- sample(letters[1:4], 250, replace=TRUE)
> b <- sample(letters[1:4], 250, replace=TRUE)
> c <- sample(letters[1:4], 250, replace=TRUE)
> d <- sample(letters[1:4], 250, replace=TRUE)
> e <- sample(letters[1:4], 250, replace=TRUE)
> df <- data.frame(a, b, c, d, e)
> result <- apply(df[,-1], 2, function(x) chisq.test(df$a, x))
> result
$b

	Pearson's Chi-squared test

data:  df$a and x 
X-squared = 8.0032, df = 9, p-value = 0.5338


$c

	Pearson's Chi-squared test

data:  df$a and x 
X-squared = 7.8289, df = 9, p-value = 0.5515


$d

	Pearson's Chi-squared test

data:  df$a and x 
X-squared = 6.1221, df = 9, p-value = 0.7276


$e

	Pearson's Chi-squared test

data:  df$a and x 
X-squared = 6.6181, df = 9, p-value = 0.6768

----------------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of jon waterhouse
Sent: Tuesday, March 06, 2012 2:16 PM
To: r-help at r-project.org
Subject: [R] How to apply two parameter function in data frame

I know this is something simple that I cannot do because I do not yet
"think"
in R.

I have a data frame has a variable participation (a factor), and several
other factors.

I want a chisq test (no contingency tables) for participation vs all of the
other factors.

In SPSS I would do:

CROSSTABS
  /TABLES= (my other factors) BY participation
  /FORMAT=NOTABLES
  /STATISTICS=CHISQ 
  /COUNT ROUND CELL.

In R I have tried something like:

mapply(chisq.test,participation,surv3[,names(surv3) %in% c('q10','q44')])

which should be effectively the same as 

chisq.test(participation,q10)
chisq.test(participation,q44)

except maybe I could store the results better....

but I get told that x and y are not the same length, and in this case,
length() of the y argument is 2, which yes, is not the number of rows in the
data frame.

I'm not sure that it is mapply, rather than lapply that I want 

Thanks,

Jon

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