Package: Dire 3.0.0

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 [aut], Ali Fathi [ctb], Claire Kelley [ctb]

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Dire.pdf |Dire.html✨
Dire/json (API)
NEWS

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

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

Pkgdown site:https://american-institutes-for-research.github.io

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

On CRAN:

Conda:

cpp

4.48 score 1 stars 2 packages 4 scripts 522 downloads 1 mentions 2 exports 42 dependencies

Last updated 1 months agofrom:ae4016d8c0. Checks:1 OK, 11 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-win-x86_64WARNINGMar 30 2025
R-4.5-mac-x86_64WARNINGMar 30 2025
R-4.5-mac-aarch64WARNINGMar 30 2025
R-4.5-linux-x86_64WARNINGMar 30 2025
R-4.4-win-x86_64WARNINGMar 30 2025
R-4.4-mac-x86_64WARNINGMar 30 2025
R-4.4-mac-aarch64WARNINGMar 30 2025
R-4.4-linux-x86_64WARNINGMar 30 2025
R-4.3-win-x86_64WARNINGMar 30 2025
R-4.3-mac-x86_64WARNINGMar 30 2025
R-4.3-mac-aarch64WARNINGMar 30 2025

Exports:drawPVsmml

Dependencies:BHbitbit64clicliprcpp11crayondata.tabledplyrfansiforcatsgenericsgluehavenhmslatticelbfgslifecyclemagrittrMASSMatrixmvnfastpillarpkgconfigprettyunitsprogresspurrrR6RcppRcppArmadilloreadrrlangstringistringrtibbletidyrtidyselecttzdbutf8vctrsvroomwithr

Weighted Marginal Maximum Likelihood Regression Estimation

Developed by Paul Bailey and Harold Doran\footnote{This publication was prepared for NCES under Contract No. ED-IES-12-D-0002 with the American Institutes for Research. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government.}

Rendered fromMML.Rmdusingknitr::rmarkdownon Mar 30 2025.

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.mmlCompositeMeans drawPVs.summary.mmlMeans
Marginal Maximum Likelihood Estimation of Linear Modelsmml