Package: prefmod 0.8-36
prefmod: Utilities to Fit Paired Comparison Models for Preferences
Generates design matrix for analysing real paired comparisons and derived paired comparison data (Likert type items/ratings or rankings) using a loglinear approach. Fits loglinear Bradley-Terry model (LLBT) exploiting an eliminate feature. Computes pattern models for paired comparisons, rankings, and ratings. Some treatment of missing values (MCAR and MNAR). Fits latent class (mixture) models for paired comparison, rating and ranking patterns using a non-parametric ML approach.
Authors:
prefmod_0.8-36.tar.gz
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prefmod.pdf |prefmod.html✨
prefmod/json (API)
NEWS
# Install 'prefmod' in R: |
install.packages('prefmod', repos = c('https://maiermarco.r-universe.dev', 'https://cloud.r-project.org')) |
- baseball - Data (paired comparisons): Baseball Games
- carconf - Data (partial rankings): Car Configurator
- cemspc - Data
- dat4 - Data (paired comparisons): dat4
- euro55.2.des - Design data frame for a paired comparison pattern model for rankings
- immig - Data (paired comparisons with undecided and forced 'NA's): Negative Attitudes towards Immigrants
- issp2000 - Data (Likert items): ISSP 2000 Survey on Environmental Issues
- music - Data
- salad - Data
- tennis - Data (paired comparisons): Preferred Interview Partner
- trdel - Data (paired comparisons): Training delivery modes
- xmpl - Data (Likert items): Example Data Set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:33d8401d75. Checks:OK: 7 NOTE: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 11 2024 |
R-4.5-win-x86_64 | NOTE | Nov 11 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 11 2024 |
R-4.4-win-x86_64 | OK | Nov 11 2024 |
R-4.4-mac-x86_64 | OK | Nov 11 2024 |
R-4.4-mac-aarch64 | OK | Nov 11 2024 |
R-4.3-win-x86_64 | OK | Nov 11 2024 |
R-4.3-mac-x86_64 | OK | Nov 11 2024 |
R-4.3-mac-aarch64 | OK | Nov 11 2024 |
Exports:checkMISexpand.matllbt.designllbt.fitllbt.worthllbtPC.fitpatt.designpatt.worthpattL.fitpattLrep.fitpattnpml.fitpattPC.fitpattR.fitpattRrep.fitplot.wmatplotworthsimPCsimR