jmv (version 0.7.3.1)

ancova: ANCOVA

Description

Analysis of Covariance

Usage

ancova(data, dep, factors = NULL, covs = NULL, modelTerms = NULL,
  ss = "3", effectSize = NULL, contrasts = NULL, plotHAxis = NULL,
  plotSepLines = NULL, plotSepPlots = NULL, postHoc = NULL,
  postHocCorr = list("tukey"), descStats = FALSE, homo = FALSE,
  qq = FALSE, plotError = "ci", ciWidth = 95)

Arguments

data

the data as a data frame

dep

a string naming the dependent variable from data, variable must be numeric

factors

a vector of strings naming the fixed factors from data

covs

a vector of strings naming the covariates from data

modelTerms

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

ss

'1', '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

contrasts

a list of lists specifying the factor and type of contrast to use, one of 'deviation', 'simple', 'difference', 'helmert', 'repeated' or 'polynomial'

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

postHoc

a list of terms to perform post-hoc tests on

postHocCorr

one or more of 'none', 'tukey', 'scheffe', 'bonf', or 'holm'; provide no, Tukey, Scheffe, Bonferroni, and Holm Post Hoc corrections respectively

descStats

TRUE or FALSE (default), provide descriptive statistics

homo

TRUE or FALSE (default), perform homogeneity tests

qq

TRUE or FALSE (default), provide a Q-Q plot of residuals

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

Examples

data('ToothGrowth')

ancova(ToothGrowth, dep = 'len', factors = 'supp', covs = 'dose')

#
#  ANCOVA
#
#  ANCOVA
#  -----------------------------------------------------------------------
#                 Sum of Squares    df    Mean Square    F        p
#  -----------------------------------------------------------------------
#    supp                    205     1          205.4     11.4     0.001
#    dose                   2224     1         2224.3    124.0    < .001
#    Residuals              1023    57           17.9
#  -----------------------------------------------------------------------
#