languageR (version 1.6)

acf.fnc: Autocorrelation trellis graph

Description

This function creates a trellis plot with autocorrelation functions for by-subject sequential dependencies in response latencies.

Usage

acf.fnc(dat, group="Subject", time="Trial", x = "RT", plot=TRUE, ...)

Value

If plot=TRUE, a trellis graph, otherwise a data frame with as column names

Lag

Autocorrelation lag

Acf

Autocorrelation

Subject

The grouping factor, typically Subject

ci

The (approximate) 95% confidence interval.

Arguments

dat

A data frame with (minimally) a grouping factor, an index for successive trails/events, and a behavioral measure

group

A grouping factor such as Subject

time

A sequential time measure such as Trial number in the experimental list

x

The dependent variable, usually a chronometric measure such as RT

plot

If true, a trellis graph is produced, otherwise a data frame with the data on which the trellis graph is based is returned

...

other optional arguments, such as layout

Author

R. H. Baayen

References

R. H. Baayen (2001) Word Frequency Distributions, Dordrecht: Kluwer.

See Also

lags.fnc

Examples

if (FALSE) {
data(beginningReaders)
acf.fnc(beginningReaders, x="LogRT")   # autocorrelations even though nonword responses not included
}