Package: GLMMRR 0.5.0
Konrad Klotzke
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>.
Authors:
GLMMRR_0.5.0.tar.gz
GLMMRR_0.5.0.tar.gz(r-4.5-noble)GLMMRR_0.5.0.tar.gz(r-4.4-noble)
GLMMRR_0.5.0.tgz(r-4.4-emscripten)GLMMRR_0.5.0.tgz(r-4.3-emscripten)
GLMMRR.pdf |GLMMRR.html✨
GLMMRR/json (API)
# Install 'GLMMRR' in R: |
install.packages('GLMMRR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- ETHBE - Online Survey on "Exams and Written Papers"
- MTURK - MTurk Survey on "Mood and Personality"
- Plagiarism - An Experimental Survey Measuring Plagiarism Using the Crosswise Model
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:59590e9e81. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 19 2024 |
R-4.5-linux | NOTE | Nov 19 2024 |
Exports:getCellMeansgetCellSizesgetMLPrevalencegetRRparametersgetUniqueGroupsintDotplotRRbinomialRRglmRRglmerRRglmGOFRRlink.cauchitRRlink.cloglogRRlink.logitRRlink.probit
Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrRColorBrewerRcppRcppEigen