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LagSequential  

Lag-Sequential Categorical Data Analysis
View on CRAN: Click here


Download and install LagSequential package within the R console
Install from CRAN:
install.packages("LagSequential")

Install from Github:
library("remotes")
install_github("cran/LagSequential")

Install by package version:
library("remotes")
install_version("LagSequential", "0.1.1")



Attach the package and use:
library("LagSequential")
Maintained by
Brian P. O'Connor
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-16
Latest Update: 2019-05-16
Description:
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) , O'Connor (1999) , Wampold & Margolin (1982) , and Wampold (1995, ISBN:0-89391-919-5).
How to cite:
Brian P. O'Connor (2019). LagSequential: Lag-Sequential Categorical Data Analysis. R package version 0.1.1, https://cran.r-project.org/web/packages/LagSequential. Accessed 25 Jun. 2026.
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Complete documentation for LagSequential
Functions, R codes and Examples using the LagSequential R package
Some associated functions: LagSequential-package . bidirectional . data_Wampold_1982 . data_Wampold_1984 . data_seqgroups_numeric . data_seqgroups_strings . data_sequential . nonparadom . paradom . seqgroups . sequential . twocells . 
Some associated R codes: bidirectional.R . nonparadom.R . paradom.R . seqgroups.R . sequential.R . twocells.R .  Full LagSequential package functions and examples
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