ezAnalysis: Compute ANOVA, LMM, or t-test

In thomas-hinterecker/Ragbu: This package includes useful functions for data analysis in cognitive science

Description

This function provides easy analysis of data from factorial experiments, including purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss designs, and mixed within-and-between-Ss designs, yielding either Linear mixed effect model, ANOVA or t-test results, as well as effect sizes and assumption checks.

Usage

ezAnalysis(data, dv, wid = NULL, within = NULL, between = NULL,
  test = "aov", options = list(random_effects = NULL, contrasts = NULL, ddf
  = "Satterthwaite", sph.cor = "GG", mau.p = 0.05, peta = TRUE),
  return_obj = FALSE, print = TRUE, dfsep = ", ")

Arguments

data	Data frame containing the data to be analyzed.
dv	Name of the column in data that contains the dependent variable. Values in this column must be numeric.
wid	Name of the column in data that contains the variable specifying the case/Ss identifier. This should be a unique value per case/Ss.
within	Names of columns in data that contain predictor variables that are manipulated (or observed) within-Ss. If a single value, may be specified by name alone; if multiple values, must be specified as a .() list.
between	Names of columns in data that contain predictor variables that are manipulated (or observed) between-Ss. If a single value, may be specified by name alone; if multiple values, must be specified as a .() list.
test	Use this parameter to specify the test that should be run. (aov = ANOVA, lmer = linear mixed effects model)
options	Use this parameter to specify the test options. For lmer these are random_effects, contrasts and ddf. For aov sph.cor and mau.p
return_obj	Set this parameter to TRUE if you want that the analysis model is returned as function value.
print	Set this parameter to FALSE if the function should not print the results.
dfsep	This specifies the seperator used to seperator the df values in the formatted results. By default, a comma is used.
random_effects	LMER parameter: Use this parameter to specify a more complex random effects term of a linear mixed effects model. The given value must be of type string.
contrasts	LMER parameter: Use this paramater to specify a list of contrasts for the fixed effects factors in a linear mixed effects model.
ddf	LMER parameter: This specifies the method used for calculating p-values of the fixed effects of the linear mixed model (Satterthwaite, Kenward-Roger, etc.).
sph.cor	ANOVA parameter: Use this paramater to specify the correction estimates to use for sphericity corrections of within factors of a ANOVA (GG, HF, no; default="GG").
mau.p	ANOVA parameter: Use this paramater to specify the threshold for Mauchly's test of sphericity (default=0.05).

Value

Model object (optional)

thomas-hinterecker/Ragbu documentation built on May 8, 2019, 9:46 a.m.