Package: DMAR
Type: Package
Title: Design, Measurement, and Analysis in R (DMAR)
Version: 1.0.0
Date: 2026-09-07
Authors@R: c(person("Ken", "Kelley", role = c("aut", "cre"),
                    email = "kkelley@nd.edu",
                    comment = c(ORCID = "0000-0002-4756-8360")))
Imports: grDevices, MASS, generics, parallel, stats, utils, withr
Suggests: boot, car, ggplot2 (>= 3.4.0), ggrain, knitr, lavaan (>=
        0.7-2), lme4, lmerTest, mvtnorm, nlme, OpenMx, patchwork,
        reformulas, rmarkdown, testthat (>= 3.2.0)
Description: Methods for design, measurement, and analysis, with the
        aim of being user friendly yet methodologically sound. 'DMAR'
        (pronounced "Dee-Mar") implements many advanced and nonstandard
        methods and makes them available for straightforward use, with
        interfaces, defaults, and documentation that are consistent
        across the package and grounded in the methodological
        literature, in support of sound and reproducible results. The
        package emphasizes effect size estimation with confidence
        intervals; sample size planning through accuracy in parameter
        estimation (AIPE) and power analysis (including composite power
        for designs whose conclusions require several results to hold
        at once), with minimum risk, sequential, and equivalence
        frameworks; reliability, agreement, and measurement more
        broadly, from coefficient omega with confidence intervals to
        measurement invariance; factor analysis and structural equation
        modeling, in which constructs, latent variables measured by
        multiple indicators, are modeled directly, with confirmatory
        factor analysis, convergent and discriminant validity, and
        sample size planning for structural equation models; mediation
        analysis, from the simple mediation model with bootstrap
        intervals to likelihood ratio tests of arbitrary indirect
        effects by model-based constrained optimization (MBCO), with
        multiple groups and the probing of moderated mediation;
        equivalence and noninferiority testing; meta-analysis; repeated
        measures, multivariate, ANOVA, and ANCOVA designs; and
        inference grounded in model comparison throughout. Measurement
        is approached from a psychometric perspective, and although
        many of the methods grew up in human-centered research, they
        apply broadly across the empirical sciences. Much of what is
        implemented traces to the author's methodological work,
        interests, and collaborations. 'DMAR' is a more modern, more
        general, and greatly expanded reimagining of the 'MBESS'
        package (Kelley, 2007a, <doi:10.18637/jss.v020.i08>; 2007b,
        <doi:10.3758/BF03192993>), which has been on CRAN for more than
        two decades and remains available there in stable form. Most
        functions accept either raw data or the summary statistics
        typically reported in published articles, so an analysis can be
        reproduced from a paper without the original data, which is
        useful both for extending a published analysis and for
        meta-analytic work. The estimation, inference, and planning
        functions return one consistently formatted data frame per
        function that composes with the broader R ecosystem, and
        confidence intervals are reported alongside effect sizes
        throughout, as best practice recommends. Researchers who have
        data and a question but who are not R experts will find the
        package approachable, while methodologists gain access to
        advanced and nonstandard methods, including tables of critical
        values not available elsewhere.
Depends: R (>= 4.0.0)
URL: https://kenkelley.org, https://yelleknek.github.io/DMAR/,
        https://github.com/yelleKneK/DMAR
BugReports: https://github.com/yelleKneK/DMAR/issues
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/testthat/parallel: true
Config/testthat/start-first: ss_aipe_crd_es,
        reliability_omega_categorical, cv_bryant_paulson, ci_dunnett,
        reliability_omega, ss_power_composite_sem,
        ss_aipe_composite_sem, mediation_mbco,
        ss_aipe_new_sensitivities
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-09-22 00:21:10 UTC; root
Author: Ken Kelley [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-4756-8360>)
Maintainer: Ken Kelley <kkelley@nd.edu>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-09-21 20:50:14 UTC
RemoteUrl: https://github.com/cran/DMAR
RemoteRef: HEAD
RemoteSha: cc8137c7f87c75ea4d2b07774abd9a351b271f3a
Built: R 4.6.0; ; 2026-09-22 00:25:14 UTC; unix
