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solomonR 0.3.0

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@JUhalt JUhalt released this 15 Sep 23:32
· 262 commits to master since this release
v0.3.0
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Learn about vigilant mode.

solomonR 0.3.0

solomonR 0.3.0 is aimed at graduate students and applied researchers who analyze, interpret, and report Solomon four-group studies.

  • Inference: corrects small-sample inference and reports confidence intervals throughout.
  • New tools: equivalence testing for pretest sensitization, design and missingness checks, and side-by-side method comparison.
  • Documentation: records where each procedure comes from and what evidence supports it.

Highlights

Getting started

  • New article, Getting Started: Analyzing a Solomon Four-Group Study (#17)
  • New solomon_example teaching data with known true effects; solomon_demo kept as a second example (#21)

Inference

  • Confidence intervals for GLM, classic Tests A-H, maximum-likelihood, and SEM effect summaries, with reference distributions chosen from the literature (#8)
  • fit_solomon_glm() defaults to HC3 standard errors with t reference distributions (#8)
  • CR2 cluster-robust tests use Satterthwaite degrees of freedom (#14)
  • fit_solomon_ml(inference = "satterthwaite"): a small-sample option validated by simulation, with a warning when the smallest cell has fewer than 40 participants (#22)
  • perm_solomon() refuses cluster-randomized fits (#15); the latent SEM mean structure is identified (#16)

New analyses and checks

  • equivalence_solomon(): two one-sided tests (TOST) for sensitization and other Solomon contrasts (#4)
  • compare_solomon_methods(): estimates, assumptions, reference distributions, and intervals aligned across methods (#7)
  • validate_solomon() and check_solomon_missing(): design coding, cell structure, and structural versus incidental missingness (#5, #6)

Research grounding and validation

  • New article on the origin, estimand, assumptions, and evidence for each Solomon method (#9)
  • New article, Validating fit_solomon_ml(): a pre-specified simulation study (84 scenarios, 2,000 replications each) with its script and results (#10, #22)
  • Help pages cite the methodological sources they implement; citations were checked against Crossref

Changes that can alter results

  • fit_solomon_glm() uses HC3 unless robust is supplied, and Gaussian tests use t with residual degrees of freedom.
  • Latent SEM means are relative to a reference group. Solomon contrasts are unchanged; model degrees of freedom and fit indices change.
  • The Groups 3-4 Hedges' g interval uses the noncentral t method.
  • Invalid design coding, permutation of clustered fits, and invalid conf_level values now raise errors.
  • Result tables gain df, conf.low, and conf.high columns.

License

Starting with 0.3.0, solomonR is licensed under the GNU General Public License, version 3 only (SPDX: GPL-3.0-only). Version 0.2.0 and earlier remain under their original MIT license.

Checks

Installation

install.packages(
  "solomonR",
  repos = c(
    JUhalt = "https://juhalt.r-universe.dev",
    CRAN = "https://cloud.r-project.org"
  )
)

or

pak::pak("JUhalt/solomonR@v0.3.0")

Not in this release

  • power_solomon() remains experimental; a validated rebuild is planned for v0.4.0 (#18).
  • Cluster-level randomization inference is planned for v0.5.0 (#19).
  • Bell-McCaffrey (HC2) intervals are under evaluation.
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