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GLMMRR: Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data
Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data. Includes Cauchit, Compl. Log-Log, Logistic, and Probit link functions for Bernoulli Distributed RR data. RR Designs: Warner, Forced Response, Unrelated Question, Kuk, Crosswise, and Triangular. Reference: Fox, J-P, Veen, D. and Klotzke, K. (2018). Generalized Linear Mixed Models for Randomized Responses. Methodology. <doi:10.1027/1614-2241/a000153>.
Getting started
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Package details |
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| Author | Jean-Paul Fox [aut, cre], Konrad Klotzke [aut], Duco Veen [aut] |
| Maintainer | Jean-Paul Fox <jpfox00@gmail.com> |
| License | GPL-3 |
| Version | 0.6.0 |
| Package repository | View on CRAN |
| Installation |
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