languageR (version 0.2)

quasiF.fnc: Quasi-F test

Description

The textbook Quasi-F test for a split-plot design with subjects, items, and a single factorial predictor. Included for educational purposes for this specific design only.

Usage

quasiF.fnc(ms1, ms2, ms3, ms4, df1, df2, df3, df4)

Arguments

ms1

Mean squares Factor

ms2

Mean squares Item:Subject

ms3

Mean squares Factor:Subject

ms4

Mean squares Item

df1

Degrees of freedom Factor

df2

Degrees of freedom Item:Subject

df3

Degrees of freedom Factor:Subject

df4

Degrees of freedom Item

Value

• A list with components
• F
  Quasi-F value.
• df1
  degrees of freedom numerator.
• df2
  degrees of freedom denominator.
• p
  p-value.

See Also

~~objects to See Also as quasiF.split.plot.fnc.

Examples

data(splitplot)

  splitplot.lm = lm(RT ~ SOA + Item + Subject + 
     SOA:Subject + Item:Subject, data = splitplot)
  splitplot.aov = anova(splitplot.lm)

  quasiF.fnc(splitplot.aov["SOA","Mean Sq"], 
     splitplot.aov["Item:Subject", "Mean Sq"],
     splitplot.aov["SOA:Subject", "Mean Sq"], 
     splitplot.aov["Item", "Mean Sq"],
     splitplot.aov["SOA","Df"], 
     splitplot.aov["Item:Subject", "Df"],
     splitplot.aov["SOA:Subject", "Df"], 
     splitplot.aov["Item", "Df"])

  # much simpler is
  quasiF.split.plot.fnc(splitplot)$quasiF