Getting started with colleyRstats

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colleyRstats helps streamline a typical analysis workflow: configure a session, check assumptions, create a plot, and generate manuscript-ready text.

Session setup

colleyRstats::colleyRstats_setup(
  set_options = FALSE,
  set_theme = FALSE,
  set_conflicts = FALSE,
  print_citation = FALSE,
  verbose = FALSE
)
#> Registered S3 methods overwritten by 'ggpp':
#>   method                  from   
#>   heightDetails.titleGrob ggplot2
#>   widthDetails.titleGrob  ggplot2

Example data

set.seed(123)

main_df <- data.frame(
  Participant = factor(rep(1:20, each = 2)),
  ConditionID = factor(rep(c("Control", "Treatment"), times = 20)),
  score = rnorm(40, mean = rep(c(50, 55), times = 20), sd = 8)
)

Check assumptions

colleyRstats::check_normality_by_group(main_df, "ConditionID", "score")
#> [1] TRUE
#> attr(,"tests")
#>   ConditionID         W   p_value
#> 1     Control 0.9378270 0.2180765
#> 2   Treatment 0.9667112 0.6844808
colleyRstats::check_homogeneity_by_group(main_df, "ConditionID", "score")
#> [1] TRUE
#> attr(,"test")
#>   df1 df2 statistic         p
#> 1   1  38 0.1081505 0.7440653

Create a plot

colleyRstats::generateEffectPlot(
  data = transform(main_df, Group = ConditionID),
  x = "ConditionID",
  y = "score",
  fillColourGroup = "Group",
  ytext = "Score",
  xtext = "Condition"
)
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?

Produce a reporting sentence

art_summary <- data.frame(
  Effect = "ConditionID",
  Df = 1,
  `F value` = 5.42,
  `Pr(>F)` = 0.027,
  Df.res = 19,
  check.names = FALSE
)

colleyRstats::reportART(art_summary, dv = "score")
#> The ART found a significant main effect of \ConditionID on score (\F{1}{19}{5.42}, \p{0.027}, $\eta_{p}^{2}$ = 0.22, 95\% CI: [0.01, 1.00]).

Next steps

Browse the reference for reporting helpers such as reportMeanAndSD() and reportDunnTest().
Use generateMoboPlot() or generateMoboPlot2() for optimization studies.
See the README for a broader catalog of available helpers.

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.
Health stats visible at Monitor.