Writing functions – Part two

The problem

One of the great things about R Markdown is the “in-line code” option, whereby, instead of typing numbers, you can insert the code for the value you wish to report, and when the document is compiled, the correct number is reported.

However, the reporting of a p value in APA format varies depending on what the p value actually is. It is consistently reported to three decimal places, with no “zero” preceding the decimal point. Values less than “.001” are reported as: “p < .001.” For example, a p value of “.8368621” would be reported as “p = .837”; while a p value of “.0000725” would be reported as “p < .001”.

The specific formatting requirements, and the variation in the reporting of the p value depending on the value being reported means that simply including in-line code to generate the p value is not always sufficient.

The solution

In order to remove the need tweak the formatting each time I report a new p value, I have created a function to do it for me.¹

*p* `r paste(p_report(p1))`

p_report <- function(x){

      # create an object "e" which contains x, the p value you are reporting,
      # rounded to 3 decimal places

  e <- round(x, digits = 3)

      # the next two lines of code prints "< .001" if x is indeed less than .001

  if (x < 0.001)
    print(paste0("<", " ", ".001"))

      # if x is greater than .001, the code below prints the object "e"
      # with an "=" sign, and with the preceeding zero removed

  else
    print(
      paste0("=",
                 " ",
                 sub("^(-?)0.", "\\1.", sprintf("%.3f",e))))

}

Preparing the dataset

First we need to load the dataset and make it (more) usable.

      # create a dataframe df, containing the airquality dataset

df <- airquality

      # change the class of df$Month from "integer" to "factor"

df$Month <- as.factor(df$Month)

Wind

We can test for differences in wind speed depending on Month. Run an anova and save the p value in an object b.

    # create an object "aov" containing the summary of the anova

aov <- summary(aov(Wind~Month, data = df))

    # create an object "b" containing the p value of aov

b <- aov[[1]][["Pr(>F)"]][1]

The output of aovis:

##              Df Sum Sq Mean Sq F value  Pr(>F)   
## Month         4  164.3   41.07   3.529 0.00879 **
## Residuals   148 1722.3   11.64                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

As you can see, the p value is 0.00879.

Including b in-line returns 0.0087901, however if we pass b through p_report() by enclosing paste(p_report(b)) in r denoted back ticks. Typing the following in an R Markdown document:

*p* `r paste(p_report(b))`

returns: p = .009.

Temp

Similarly, we can test for differences in temperature depending on Month. By using the same names for the objects, we can use the same in-line code to report the p values.

    # create an object "aov" containing the summary of the anova

aov <- summary(aov(Temp~Month, data = df))

    # create an object "b" containing the p value of aov

b <- aov[[1]][["Pr(>F)"]][1]

The output of aovis:

##              Df Sum Sq Mean Sq F value Pr(>F)    
## Month         4   7061  1765.3   39.85 <2e-16 ***
## Residuals   148   6557    44.3                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

As you can see, the p value is <2e-16.

When this is run through p_report() using:

*p* `r paste(p_report(b))`

which will return: “p < .001”.

Conclusion

The p_report() function is an example of using R to make your workflow easier. R Markdown replaces the need to type the numbers you report with the option of including in-line code to generate these numbers. p_report() means that you do not have to worry about formatting issues when these numbers are reported. Depending on how you structure your code chunks around your writing, and how name your objects, it may be possible to recycle sections of in-line code, speeding up the writing process. Furthermore, the principle behind p_report() can be applied to the writing of other functions (e.g., reporting F values or \(\chi\)²).

References