# quasiF.fnc: Quasi-F test In languageR: Data sets and functions with "Analyzing Linguistic Data: A practical introduction to statistics".

## Description

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

## Usage

 `1` ```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.

## Author(s)

R. H. Baayen

See Also as `quasiFsim.fnc`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17``` ``` data(quasif) quasif.lm = lm(RT ~ SOA + Item + Subject + SOA:Subject + Item:Subject, data = quasif) quasif.aov = anova(quasif.lm) quasiF.fnc(quasif.aov["SOA","Mean Sq"], quasif.aov["Item:Subject", "Mean Sq"], quasif.aov["SOA:Subject", "Mean Sq"], quasif.aov["Item", "Mean Sq"], quasif.aov["SOA","Df"], quasif.aov["Item:Subject", "Df"], quasif.aov["SOA:Subject", "Df"], quasif.aov["Item", "Df"]) # much simpler is quasiFsim.fnc(quasif)\$quasiF ```