WAnova (version 0.4.0)

welch_anova.test: welch_anova.test

Description

Welch's one-way ANOVA with fixed effects (between subjects analysis) from summary statistics with unequal (unknown) variances.

Usage

welch_anova.test(levels, n, means, sd, effsize = "AnL")

Value

A list of class "wAnova" that contains the F-value, df-between, df-within, p-value and effect size omega-squared that can later be converted to a table-styled summary using summary()

The adjusted omega squared estimator of the effect size is either calculated by the formula of of Albers and Lakens, Kirk or Caroll and Nordholm (Further notes see README file)

Albers, C., & Lakens, D. (2018). When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias. Journal of Experimental Social Psychology, 74, 187–195. Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56(5), 746-759. Carroll, R. M., & Nordholm, L. A. (1975). Sampling characteristics of Kelley's epsilon and Hays' omega Educational and Psychological Measurement, 35(3), 541-554.

Arguments

levels

Vector with level names of the independent variable

n

Vector with sample size for each level

means

Vector with sample mean for each level

sd

Vector with sample standard deviation for each level

effsize

Options "AnL" (standard), "Kirk", "CaN" (see below)

Examples

# \donttest{
probe_data <- data.frame(
  group = c("probe_a", "probe_b", "probe_c"),
  size = c(10, 9, 8),
  mean = c(43.00000, 33.44444, 35.75000),
  sd = c(4.027682, 9.302031, 16.298554)
)
result <- welch_anova.test(
  levels = probe_data$group,
  n = probe_data$size,
  means = probe_data$mean,
  sd = probe_data$sd,
  effsize = "Kirk"
)
summary(result)
# }