R Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses. The R package multgee implements the local odds ratios generalized estimating equations (GEE) approach proposed by Touloumis et al. (2013), a GEE approach for correlated multinomial responses that circumvents theoretical and practical limitations of the GEE method. A main strength of multgee is that it provides GEE routines for both ordinal (ordLORgee) and nominal (nomLORgee) responses, while relevant softwares in R and SAS are restricted to ordinal responses under a marginal cumulative link model specification. In addition, multgee offers a marginal adjacent categories logit model for ordinal responses and a marginal baseline category logit model for nominal. Further, utility functions are available to ease the local odds ratios structure selection (intrinsic.pars) and to perform a Wald type goodness-of-fit test between two nested GEE models (waldts). We demonstrate the application of multgee through a clinical trial with clustered ordinal multinomial responses.
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References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Nikoloulopoulos, Aristidis K.: Weighted scores estimating equations and CL1 information criteria for longitudinal ordinal response (2020)
- da Silva, José L. P.; Colosimo, Enrico A.; Demarqui, Fábio N.: A general GEE framework for the analysis of longitudinal ordinal missing data and related issues (2019)
- Inan, G.; Yucel, R.: Joint GEEs for multivariate correlated data with incomplete binary outcomes (2017)
- Anestis Touloumis: R Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses (2014) arXiv
- Nooraee, Nazanin; Molenberghs, Geert; van den Heuvel, Edwin R.: GEE for longitudinal ordinal data: comparing R-geepack, R-multgee, R-repolr, SAS-GENMOD, SPSS-GENLIN (2014)