wilcox.test loop through variable names

Often I perform the same task on a series of variables in a dataframe,
by looping through a character vector that holds the names and using
paste(), eval(), and parse() inside the loop.

For instance:

rm(environmental)
thesevars<-names(environmental)
environmental$ToyReal <-rnorm(nrow(environmental)) 
environmental$ToyDichot<- environmental$ToyReal < 0.53

tableOfResults<-data.frame(var=thesevars)

tableOfResults$p_wilcox <- NA

tableOfResults$Beta_lm <- NA

rownames(tableOfResults)<-thesevars

for( thisvar in thesevars) {
  	thiscommand<- paste("thiswilcox <- wilcox.test (", thisvar, " ~ ToyDichot , data=environmental)")
 	eval(parse(text=thiscommand))
  	tableOfResults[thisvar, "p_wilcox"] <- thiswilcox$p.value
 	thislm<-lm( environmental[ c( "ToyReal", thisvar )])
  	tableOfResults[thisvar, "Beta_lm"] <- coef(thislm)[thisvar]
}

print(tableOfResults)

Of course, the loop above is a toy example. In real life I might first
figure out whether the variable is
continuous, dichotomous, or categorical taking on several values, then
perform an operation depending on
its type.

The use of paste(), eval(), and parse() seems awkward.  As Gabor
Grothendieck showed
(http://tolstoy.newcastle.edu.au/R/e8/help/09/11/4520.html), if we
are calling a regression function such as lm() we can avoid using
paste(), as shown above.

But is there a way to avoid paste() and eval() when one uses t.test()
or wilcox.test()?