anovaRM {jmv}R Documentation

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"), descStats = FALSE,
  emMeans = list(list()), ciEmm = TRUE, ciWidthEmm = 95,
  emmPlots = TRUE, emmTables = FALSE, emmWeights = TRUE)

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 eta², partial eta², and omega² 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

descStats

TRUE or FALSE (default), provide descriptive statistics

emMeans

a list of lists specifying the variables for which the estimated marginal means need to be calculate. Supports up to three variables per term.

ciEmm

TRUE (default) or FALSE, provide a confidence interval for the estimated marginal means

ciWidthEmm

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

emmPlots

TRUE (default) or FALSE, provide estimated marginal means plots

emmTables

TRUE or FALSE (default), provide estimated marginal means tables

emmWeights

TRUE (default) or FALSE, weigh each cell equally or weigh them according to the cell frequency

Value

A results object containing:

results$rmTable a table
results$bsTable a table
results$assump$spherTable a table
results$assump$leveneTable a table
results$contrasts an array of tables
results$postHoc an array of tables
results$emm an array of the estimated marginal means plots + tables

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$rmTable$asDF

as.data.frame(results$rmTable)

Examples

## Not run: 

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

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

#
#  REPEATED MEASURES ANOVA
#
#  Within Subjects Effects
#  -----------------------------------------------------------------------
#                  Sum of Squares    df    Mean Square    F       p
#  -----------------------------------------------------------------------
#    Frightening              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
#

## End(Not run)
[Package jmv version 0.9.2.0 Index]