Package: Dire 2.2.0

Paul Bailey

Dire: Linear Regressions with a Latent Outcome Variable

Fit latent variable linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, a latent distribution is conditional on students item response, item characteristics, and conditioning variables the user includes. This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <https://am.air.org/>. As of version 2, also allows the user to draw plausible values.

Authors:Emmanuel Sikali [pdr], Paul Bailey [aut, cre], Eric Buehler [aut], Sun-joo Lee [aut], Harold Doran [aut], Blue Webb [ctb], Claire Kelley [ctb]

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NEWS

# Install 'Dire' in R:
install.packages('Dire', repos = c('https://american-institutes-for-research.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/american-institutes-for-research/dire/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

2 exports 1 stars 1.60 score 36 dependencies 2 dependents 1 mentions 3 scripts 431 downloads

Last updated 11 months agofrom:2dbe7e4dc0. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 27 2024
R-4.5-win-x86_64WARNINGAug 27 2024
R-4.5-linux-x86_64WARNINGAug 27 2024
R-4.4-win-x86_64WARNINGAug 27 2024
R-4.4-mac-x86_64WARNINGAug 27 2024
R-4.4-mac-aarch64WARNINGAug 27 2024
R-4.3-win-x86_64WARNINGAug 27 2024
R-4.3-mac-x86_64WARNINGAug 27 2024
R-4.3-mac-aarch64WARNINGAug 27 2024

Exports:drawPVsmml

Dependencies:bitbit64clicliprcodetoolscpp11crayonfansiforcatsforeachgluehavenhmsiteratorslatticelbfgslifecyclemagrittrMASSMatrixpillarpkgconfigprettyunitsprogressR6RcppRcppArmadilloreadrrlangtibbletidyselecttzdbutf8vctrsvroomwithr

Weighted Marginal Maximum Likelihood Regression Estimation

Rendered fromMML.Rmdusingknitr::rmarkdownon Aug 27 2024.

Last update: 2023-06-16
Started: 2021-03-19

Readme and manuals

Help Manual

Help pageTopics
Draw plausible values (PVs) from an mml fitdrawPVs drawPVs.mmlCompositeMeans drawPVs.mmlMeans drawPVs.summary.mmlMeans
Marginal Maximum Likelihood Estimation of Linear Modelsmml