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Last data update: 2014.03.03

R: Autocorrelation trellis graph

acf.fnc

R Documentation

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, ...)

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`

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.

Author(s)

R. H. Baayen

References

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

Examples

## Not run: 
data(beginningReaders)
acf.fnc(beginningReaders, x="LogRT")   # autocorrelations even though nonword responses not included

## End(Not run)