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prmisc

Miscellaneous printing of statistical results in Rmarkdown according to APA style guidelines. This package covers some basic statistical tests (t-test, ANOVA, correlation, chi-squared test) and some basic number printing manipulations (formatting p-values, removing leading zeros for numbers that cannot be greater than one, and others). For more printing functions in R markdown documents see the R package papaja.

Installation

library("devtools") # if not available: install.packages("devtools")
install_github("m-Py/prmisc")

# load the package via
library("prmisc")

Usage

t.test

ttest <- t.test(1:10, y = c(7:20), var.equal = TRUE)
library("effectsize") # for Cohen's d
cohend <- cohens_d(1:10, c(7:20))
print_ttest(ttest, cohend) # include this call in Rmd inline code

# [1] "$t(22) = -5.15$, $p < .001$, $d = -2.13$"

# An example for paired data:
data(sleep) # ?sleep
tt <- t.test(sleep$extra[sleep$group == 1], 
             sleep$extra[sleep$group == 2], paired = TRUE)
cd <- cohens_d(sleep$extra[sleep$group == 1], 
               sleep$extra[sleep$group == 2], paired = TRUE)
print_ttest(tt, cd)
# "$t(9) = -4.06$, $p = .003$, $d_z = -1.28$"

# Print the confidence interval:
print_ttest(tt, cd, confidence = TRUE)
# "$t(9) = -4.06$, $p = .003$, $d_z = -1.28$, $95\\%$ $CI$ $[-2.12$, $-0.41]$"

# The information about the CI is taken from the effectsize object:
cd <- cohens_d(sleep$extra[sleep$group == 1], 
               sleep$extra[sleep$group == 2], paired = TRUE, ci = .8)
print_ttest(tt, cd, confidence = TRUE)
# "$t(9) = -4.06$, $p = .003$, $d_z = -1.28$, $80\\%$ $CI$ $[-1.81$, $-0.70]$"

# effect size object can be left out:
print_ttest(tt)
# "$t(9) = -4.06$, $p = .003$"

# Each function includes documentation via the R help:
?print_ttest

chi-square-test

x <- matrix(c(12, 5, 7, 7), ncol = 2)
print_chi2(x) # does not use continuity correction by default
# [1] "$\\chi^2(1, N = 31) = 1.37$, $p = .242$, $\\phi = .21$"

print_chi2(x, correct = TRUE) # use continuity correction
# [1] "$\\chi^2(1, N = 31) = 0.64$, $p = .423$, $\\phi = .14$"

Correlation coefficient

x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c( 2.6,  3.1,  2.5,  5.0,  3.6,  4.0,  5.2,  2.8,  3.8)
cor_results <- cor.test(x, y)

print_cortest(cor_results)
# [1] "$r(7) = .57$, $p = .108$"

ANOVA

library("afex")
# see ?aov_ez
data(md_12.1)
aov_results <- aov_ez("id", "rt", md_12.1, within = c("angle", "noise"))

print_anova(aov_results) # returns a list with all effects in this ANOVA
# $angle
# [1] "$F(1.92$, $17.31) = 40.72$, $p < .001$, $\\eta_G^2 = .39$"
# 
# $noise
# [1] "$F(1$, $9) = 33.77$, $p < .001$, $\\eta_G^2 = .39$"
# 
# $`angle:noise`
# [1] "$F(1.81$, $16.27) = 45.31$, $p < .001$, $\\eta_G^2 = .19$"

## Print nonitalic eta, which is required according to APA guidelines
print_anova(aov_results, italic_eta = FALSE)
# $angle
# [1] "$F(1.92$, $17.31) = 40.72$, $p < .001$, $\\upeta_\\mathrm{G}^2 = .39$"
#
# $noise
# [1] "$F(1$, $9) = 33.77$, $p < .001$, $\\upeta_\\mathrm{G}^2 = .39$"
# 
# $`angle:noise`
# [1] "$F(1.81$, $16.27) = 45.31$, $p < .001$, $\\upeta_\\mathrm{G}^2 = .19$"


## Example using other (or no) effect size index (output not shown)
print_anova(aov_ez("id", "rt", md_12.1, within = c("angle", "noise"),
                   anova_table = list(es = "pes")))
print_anova(aov_ez("id", "rt", md_12.1, within = c("angle", "noise"),
                   anova_table = list(es = "none")))

Some functions for printing numbers

force_decimals(c(1.23456, 0.873, 2.3456), decimals = 2)
# [1] "1.23" "0.87" "2.35"
## Note that the function `round()` will not produce the same results as
## force_decimals in Rmd output

force_decimals(c(0.004, 0.001, 0.0005, 0.02))
# [1] "0.00" "0.00" "0.00" "0.02"
## Small numbers are rounded to zero by default.
## This behaviour can be controlled using the argument `round_zero`:
force_decimals(c(0.004, 0.001, 0.0005, 0.02), round_zero = FALSE)
# "< 0.01" "< 0.01" "< 0.01" "0.02"

## Leave integers intact:
force_or_cut(c(1:3, 1.23456, 0.873, 2.3456), decimals = 2)
# [1] "1"    "2"    "3"    "1.23" "0.87" "2.35"
## Compare:
force_decimals(c(1:3, 1.23456, 0.873, 2.3456), decimals = 2)
# [1] "1.00" "2.00" "3.00" "1.23" "0.87" "2.35"

## Show only decimals (e.g., for p-values or correlation coefficients)
decimals_only(c(0.23456, 0.873, 0.3456), decimals = 3)
# [1] ".235" ".873" ".346"

## Format a p-value, default is 3 decimals
format_p(0.03123)
# [1] "$p = .031$"

format_p(0.000001231, 3)
# [1] "$p < .001$"

format_p(0.3123, decimals = 2)
# [1] "$p = .31$"

## Format several p-values with one function call
format_p(c(0.3123, 0.001, 0.00001, 0.19))
# [1] "$p = .312$" "$p = .001$" "$p < .001$" "$p = .190$"

format_p(c(.999, .9999, 1))
# [1] "$p = .999$" "$p > .999$" "$p > .999$"

## Number printing functions have two decimals by default, 
## but format_p has three decimals by default

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.