LagSequential: Lag-Sequential Categorical Data Analysis

Lag-sequential analysis is a method of assessing of patterns (what tends to follow what?) in sequences of codes. The codes are typically for discrete behaviors or states. The functions in this package read a stream of codes, or a frequency transition matrix, and produce a variety of lag sequential statistics, including transitional frequencies, expected transitional frequencies, transitional probabilities, z values, adjusted residuals, Yule's Q values, likelihood ratio tests of stationarity across time and homogeneity across groups or segments, transformed kappas for unidirectional dependence, bidirectional dependence, parallel and nonparallel dominance, and significance levels based on both parametric and randomization tests. The methods are described in Bakeman & Quera (2011) <doi:10.1017/CBO9781139017343>, O'Connor (1999) <doi:10.3758/BF03200753>, Wampold & Margolin (1982) <doi:10.1037/0033-2909.92.3.755>, and Wampold (1995, ISBN:0-89391-919-5).

Version: 0.1.1
Depends: R (≥ 1.9.0)
Published: 2019-05-16
DOI: 10.32614/CRAN.package.LagSequential
Author: Zakary A. Draper & Brian P. O'Connor
Maintainer: Brian P. O'Connor <brian.oconnor at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: LagSequential results


Reference manual: LagSequential.pdf


Package source: LagSequential_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LagSequential_0.1.1.tgz, r-oldrel (arm64): LagSequential_0.1.1.tgz, r-release (x86_64): LagSequential_0.1.1.tgz, r-oldrel (x86_64): LagSequential_0.1.1.tgz


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