Learn R Programming

jmv (version 0.7.3.1)

anovaRM: Repeated Measures ANOVA

Description

Repeated Measures ANOVA

Usage

anovaRM(data, rm = list(list(label = "RM Factor 1", levels = list("Level 1",
  "Level 2"))), rmCells = NULL, bs = NULL, cov = NULL, rmTerms = NULL,
  bsTerms = NULL, ss = "3", effectSize = NULL, spherTests = FALSE,
  spherCorr = list("none"), leveneTest = FALSE, contrasts = NULL,
  postHoc = NULL, postHocCorr = list("tukey"), plotHAxis = NULL,
  plotSepLines = NULL, plotSepPlots = NULL, plotError = "ci",
  ciWidth = 95, descStats = FALSE)

Arguments

data

the data as a data frame

rm

a list of lists, where each list describes the label (as a string) and the levels (as vector of strings) of a particular repeated measures factor

rmCells

a list of lists, where each list decribes a repeated measure (as a string) from data defined as measure and the particular combination of levels from rm that it belongs to (as a vector of strings) defined as cell

bs

a vector of strings naming the between subjects factors from data

cov

a vector of strings naming the covariates from data. Variables must be numeric

rmTerms

a list of character vectors describing the repeated measures terms to go into the model

bsTerms

a list of character vectors describing the between subjects terms to go into the model

ss

'2' or '3' (default), the sum of squares to use

effectSize

one or more of 'eta', 'partEta', or 'omega'; use eta<U+00B2>, partial eta<U+00B2>, and omega<U+00B2> effect sizes, respectively

spherTests

TRUE or FALSE (default), perform sphericity tests

spherCorr

one or more of 'none' (default), 'GG', or HF; use no p-value correction, the Greenhouse-Geisser p-value correction, and the Huynh-Feldt p-value correction for shericity, respectively

leveneTest

TRUE or FALSE (default), test for equality of variances (i.e., Levene's test)

contrasts

in development

postHoc

a list of character vectors describing the post-hoc tests that need to be computed

postHocCorr

one or more of 'none', 'tukey' (default), 'scheffe', 'bonf', or 'holm'; use no, Tukey, Scheffe, Bonferroni and Holm posthoc corrections, respectively

plotHAxis

a string naming the variable placed on the horizontal axis of the plot

plotSepLines

a string naming the variable represented as separate lines on the plot

plotSepPlots

a string naming the variable to separate over to form multiple plots

plotError

'none', 'ci' (default), or 'se'. Use no error bars, use confidence intervals, or use standard errors on the plots, respectively

ciWidth

a number between 50 and 99.9 (default: 95) specifying the confidence interval width

descStats

TRUE or FALSE (default), provide descriptive statistics

Examples

Run this code


data('bugs', package = 'jmv')

anovaRM(
    data = bugs,
    rm = list(
        list(
            label = 'Disgusting',
            levels = c('Low', 'High'))),
    rmCells = list(
        list(
            measure = 'LDLF',
            cell = 'Low'),
        list(
            measure = 'LDHF',
            cell = 'High')),
    rmTerms = list(
        'Disgusting'))

#
#  Within Subjects Effects
#  -----------------------------------------------------------------------
#                  Sum of Squares    df    Mean Square    F       p
#  -----------------------------------------------------------------------
#    Disgusting               126     1         126.11    44.2    < .001
#    Residual                 257    90           2.85
#  -----------------------------------------------------------------------
#    Note. Type 3 Sums of Squares
#
#
#
#  Between Subjects Effects
#  -----------------------------------------------------------------
#                Sum of Squares    df    Mean Square    F    p
#  -----------------------------------------------------------------
#    Residual               954    90           10.6
#  -----------------------------------------------------------------
#    Note. Type 3 Sums of Squares
#

Run the code above in your browser using DataLab