The goal of statsreportr is to make it easy to report the results of statistical analyses in inline code of a R Markdown or Quarto document.
Installation
You can install the development version of statsreportr from GitHub with:
# install.packages("pak")
pak::pak("KyleOfCanada/statsreportr")Example
Some basic examples which shows you how to generate reports for ANOVAs and t-tests:
library(statsreportr)
# ANOVAs
results <- mtcars |>
rstatix::anova_test(mpg ~ cyl)
format_p(results$p)
#> [1] "< 0.0001"
results2 <- mtcars |>
rstatix::anova_test(mpg ~ cyl * carb)
results3 <- aov(mpg ~ cyl * carb, data = mtcars)
report_anova(results2)
#> [1] "*F*~(1,28)~ = 47.2, *p* < 0.0001, $\\eta^2_G$ = 0.628"
report_anova(results2, "carb")
#> [1] "*F*~(1,28)~ = 1.55, *p* = 0.223, $\\eta^2_G$ = 0.052"
report_anova(results2, 2)
#> [1] "*F*~(1,28)~ = 1.55, *p* = 0.223, $\\eta^2_G$ = 0.052"
report_anova(results3, 2)
#> [1] "*F*~(1,28)~ = 1.55, *p* = 0.223, $\\eta^2_G$ = 0.052"
# t-tests
results3 <- mtcars |>
rstatix::t_test(mpg ~ am)
report_t(results3)
#> [1] "*t*~(18.3)~ = -3.77, *p* = 0.00137"
results4 <- mtcars |>
rstatix::t_test(mpg ~ cyl)
cohensd4 <- mtcars |>
rstatix::cohens_d(mpg ~ cyl)
report_t(results4,
effect = c("6", "8"),
cohensd = cohensd4, cohens_magnitude = TRUE
)
#> [1] "*t*~(18.5)~ = 5.29, adjusted *p* < 0.0001, *d* = 2.23, indicating a large effect"
# Descriptive stats
mtcars |> report_mean_sd(mpg, cyl, effect = "6")
#> [1] "19.7 ± 1.45"
mtcars |> report_mean_sem(mpg, cyl, effect = "6")
#> [1] "19.7 ± 0.549"The intent of this package is to be used inline in a R Markdown or Quarto document. For example, the following inline code:
The results of the t test showed a significant difference in the mpg of 6 (`
r mtcars |> report_mean_sd(mpg, cyl, effect = "6")`) vs 8 (`r mtcars |> report_mean_sd(mpg, cyl, effect = "8")`) cylinder cars (`r report_t(results4, effect = c("6", "8"), cohensd = cohensd4, cohens_magnitude = TRUE)`).
Will render as:
The results of the t test showed a significant difference in the mpg of 6 (19.7 ± 1.45) vs 8 (15.1 ± 2.56) cylinder cars (t(18.5) = 5.29, adjusted p < 0.0001, d = 2.23, indicating a large effect).