lm_effsize_standardizer: Standardize a dataframe with effect sizes for `aov`, `lm`, `aovlist`, etc. objects.

Description

The difference between lm_effsize_ci and lm_effsize_standardizer is that the former has more opinionated column naming, while the latter doesn't. The latter can thus be more helpful in writing a wrapper around this function.

Usage

lm_effsize_standardizer(
  object,
  effsize = "eta",
  partial = TRUE,
  conf.level = 0.95,
  nboot = 500,
  method = c("dist", "quantile")
)

Arguments

object

The linear model object (can be of class lm, aov, anova, or aovlist).

effsize

Character describing the effect size to be displayed: "eta" (default) or "omega".

partial

Logical that decides if partial eta-squared or omega-squared are returned (Default: TRUE). If FALSE, eta-squared or omega-squared will be returned. Valid only for objects of class lm, aov, anova, or aovlist.

conf.level

Numeric specifying Level of confidence for the confidence interval (Default: 0.95).

nboot

Number of bootstrap samples for confidence intervals for partial eta-squared and omega-squared (Default: 500).

method

Character vector, indicating if confidence intervals should be based on bootstrap standard error, multiplied by the value of the quantile function of the t-distribution (default), or on sample quantiles of the bootstrapped values. See 'Details' in boot_ci(). May be abbreviated.

Examples

Run this code

# NOT RUN {
set.seed(123)
groupedstats::lm_effsize_standardizer(
  object = stats::lm(formula = brainwt ~ vore, data = ggplot2::msleep),
  effsize = "eta",
  partial = FALSE,
  conf.level = 0.99,
  nboot = 20
)
# }

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