R for loop with paired variables

I am new to programming (i.e., loops and if-else statements), but not new to statistics in R.

I have about 16 traits I want to compare between males and females within 5 different populations, so 5x16 comparisons. I first want to check if the male and female trait variances are equal (var.test) and then use this information to determine the correct version of the t.test function (either var = T or var = F). I am trying to write a loop to automate this process.

I wrote a functioning if-else statement:

 if ((var.test(male$mass,female$mass)$p.value < 0.05) == "TRUE") {
   t.test(male$mass,female$mass, var = F)
 } else 
   t.test(male$mass,female$mass, var = T)

But I cannot seem to figure out how to apply this to all my traits.

I don't want to use two nested for statements:

 for (i in c(male$trait1, male$trait2,...)) {
 for (j in c(female$trait1, female$trait2,...)) {
  ...
   }
 }

Because this would create a matrix performing var.test and t.test on all combinations of traits. Whereas, I want the male and female version of each trait paired only.

Here is the format of my data. I made two subsets of the data (male and female):

head(male)
id location  gens log.gens   sex   mass   head   cbl
49   Hawaii   268 2.428135     M 583.86 78.648 65.54           
27   Hawaii   268 2.428135     M 692.30 83.604 69.67
33   Hawaii   268 2.428135     M 647.70 81.180 67.65
34   Hawaii   268 2.428135     M 704.70 84.720 70.60
35   Hawaii   268 2.428135     M 604.90 82.440 68.70

Solution

I am not sure the format you hope to obtain.

Something like this will return a list

listOfTraits <- c('mass', 'head', 'cbl')
resultList <- lapply(listOfTraits, FUN = function(trait) {
  if (var.test(male[[trait]],female[[trait]])$p.value < 0.05) {
   t.test(male[[trait]],female[[trait]], var = F)
  } else{
   t.test(male[[trait]],female[[trait]], var = T)
  }
})

Second Fix

listOfTraits <- c('mass', 'head', 'cbl')
resultList <- lapply(listOfTraits, FUN = function(trait) {
  if (var.test(male[[trait]],female[[trait]])$p.value < 0.05) {
    x <-  t.test(male[[trait]],female[[trait]], var = T)
    names(x$estimate) <- c(paste0('male_',trait),paste0('female_',trait))
    x$data.name <- paste0('male_',trait, " and ",paste0('female_',trait))

  } else{
    x <- t.test(male[[trait]],female[[trait]], var = T)
    names(x$estimate) <- c(paste0('male_',trait),paste0('female_',trait))
    x$data.name <- paste0('male_',trait, " and ",paste0('female_',trait))
  }
  x
})