groupedstats (version 0.0.7)

lm_effsize_ci: Confidence intervals for partial eta-squared and omega-squared for linear models.

Description

This function will convert a linear model object to a dataframe containing statistical details for all effects along with partial eta-squared effect size and its confidence interval.

Usage

lm_effsize_ci(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.

Value

A dataframe with results from stats::lm() with partial eta-squared, omega-squared, and bootstrapped confidence interval for the same.

Examples

# NOT RUN {
# model
set.seed(123)
mod <-
  stats::aov(
    formula = mpg ~ wt + qsec + Error(disp / am),
    data = mtcars
  )

# dataframe with effect size and confidence intervals
groupedstats::lm_effsize_ci(mod)
# }