Report the model produced by nparLD. The model provided must be the model generated by the command 'nparLD' nparLD (see https://CRAN.R-project.org/package=nparLD).

#' Only significant main and interaction effects are reported. P-values are rounded for the third digit and relative treatment effects (RTE) are included when available. Attention: the independent variables of the formula and the term specifying the participant must be factors (i.e., use as.factor()).

Usage

reportNparLD(
  model,
  dv = "Testdependentvariable",
  write_to_clipboard = FALSE,
  sink_to = NULL
)

report_nparld(
  model,
  dv = "Testdependentvariable",
  write_to_clipboard = FALSE,
  sink_to = NULL
)

Arguments

model

the model

dv

the dependent variable

write_to_clipboard

whether to write to the clipboard

sink_to

optional path of a .tex file to write the sentences to, so a manuscript can \input{} them

Value

Invisibly returns the reported sentence(s) as a character vector; the text is also emitted via message().

Details

#' To easily copy and paste the results to your manuscript, the following commands must be defined in Latex: \newcommand{\F}{\textit{F=}} \newcommand{\df}{\textit{df=}} \newcommand{\p}{\textit{p=}} \newcommand{\pminor}{\textit{p$<$}}

Naming

report_nparld() is the spelling used throughout the documentation and the one to prefer in new code: the report_* / plot_* / check_* prefixes make the API discoverable through autocomplete.

reportNparLD() is the original name. Both names refer to the same function object, so they are entirely interchangeable; the original remains fully supported and is not scheduled for removal, and existing scripts keep working unchanged.

Examples

# \donttest{
if (requireNamespace("nparLD", quietly = TRUE)) {
  # Small toy data set for nparLD
  set.seed(123)
  example_data <- data.frame(
    Subject = factor(rep(1:10, each = 3)),
    Time    = factor(rep(c("T1", "T2", "T3"), times = 10)),
    # a rising trend over time, so there is something to report
    TLX1    = rep(c(45, 52, 61), times = 10) + stats::rnorm(30, sd = 4)
  )

  # Fit nparLD model
  model <- nparLD::nparLD(TLX1 ~ Time, data = example_data, subject = "Subject")

  # Report the nparLD result
  reportNparLD(model, dv = "TLX1")
}
#> The nparLD analysis found a significant main effect of \Time on TLX1 (\F{2}{$\infty$}{37.78}, \pminor{0.001}). 
# }