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cta  

Contingency Table Analysis Based on ML Fitting of MPH Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("cta", "1.3.0")



Attach the package and use:
library("cta")
Maintained by
Qiansheng Zhu
[Scholar Profile | Author Map]
First Published: 2021-08-23
Latest Update: 2021-08-23
Description:
Contingency table analysis is performed based on maximum likelihood (ML) fitting of multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models. See Lang (2004) and Lang (2005) for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood- based (cell- and link-specific) residuals; and cell probability and expected count estimates along with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood, score, power-divergence--confidence intervals for contingency table estimands, when table probabilities are potentially subject to equality constraints. For test-inversion intervals, see Lang (2008) and Zhu (2020) .
How to cite:
Qiansheng Zhu (2021). cta: Contingency Table Analysis Based on ML Fitting of MPH Models. R package version 1.3.0, https://cran.r-project.org/web/packages/cta. Accessed 07 May. 2025.
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