Writing function around statistical tests in R

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I'm writing a function for my (working) R script in order to clean up my code. I do not have experience with writing functions, but decided I should invest some time into this. The goal of my function is to perform multiple statistical tests while only passing the required dataframe, quantitative variable and grouping variable once. However, I cannot get this to work. For your reference, I'll use the ToothGrowth data frame to illustrate my problem.

Say I want to run a Kruskal-Wallis test and one-way ANOVA on len, to compare different groups named supp, for whatever reason. I can do this separately with

kruskal.test(len ~ supp, data = ToothGrowth)
aov(len ~ supp, data = ToothGrowth)

Now I want to write a function that performs both tests. This is what I had thought should work:

stat_test <- function(mydata, quantvar, groupvar) {
  kruskal.test(quantvar ~ groupvar, data = mydata)
  aov(quantvar ~ groupvar, data = mydata)
}

But if I then run stat_test(ToothGrowth, "len", "sup"), I get the error 

Error in kruskal.test.default("len", "supp") : 
  all observations are in the same group

What am I doing wrong? Any help would be much appreciated!

r function
3 Answers

It looks like you need to convert your variable arguments, given as text strings, into a formula. You can do this by concatenating the strings with paste(). Also, you will need to wrap print() around both of your statistical tests within the function, otherwise only the last one will display.

Here is the modified function:

stat_test <- function(mydata, quantvar, groupvar) {
  model_formula <- formula(paste(quantvar, '~', groupvar))
  print(kruskal.test(model_formula, data = mydata))
  print(aov(model_formula, data = mydata))
}
user_28546080

You can use deparse(substitute(quantvar)) to get the quoted name of the column you are passing to the function, and this will allow you to build a formula using paste. This is a more idiomatic way of operating in R.

Here's a reproducible example:

stat_test <- function(mydata, quantvar, groupvar) {
  A <- as.formula(paste(deparse(substitute(quantvar)), "~", 
                        deparse(substitute(groupvar))))
  print(kruskal.test(A, data = mydata))
  cat("\n--------------------------------------\n\n")
  aov(A, data = mydata)
}

stat_test(ToothGrowth, len, supp)
#> 
#>  Kruskal-Wallis rank sum test
#> 
#> data:  len by supp
#> Kruskal-Wallis chi-squared = 3.4454, df = 1, p-value = 0.06343
#> 
#> 
#> --------------------------------------
#> Call:
#>    aov(formula = A, data = mydata)
#> 
#> Terms:
#>                     supp Residuals
#> Sum of Squares   205.350  3246.859
#> Deg. of Freedom        1        58
#> 
#> Residual standard error: 7.482001
#> Estimated effects may be unbalanced

Created on 2020-03-30 by the reprex package (v0.3.0)

user_125003150

For reference, if using rstatix (tidy version of statistical functions), you need to use sym and !!, while using formula() when needed.

make_kruskal_test <- function(data, quantvar, groupvar) {
  library(rstatix, quietly = TRUE)
  library(rlang, quietly = TRUE)

  formula_expression <- formula(paste(quantvar, "~", groupvar))
  quantvar_sym <- sym(quantvar)

  shapiro <- shapiro_test(data, !!quantvar_sym) %>% print()
}

sample_data <- tibble::tibble(sample = letters[1:5], mean = 1:5)

make_kruskal_test(sample_data, "mean", "sample")

#> # A tibble: 1 x 3
#>   variable statistic     p
#>   <chr>        <dbl> <dbl>
#> 1 mean         0.987 0.967
user_183428540
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