What fit are we worried about? | Which inference routes are available? | How do I test the term anyway? | What about confidence intervals? | Where does cluster bootstrap stand? | Variance-component boundary tests | Summary | References
Package: mixeff 0.2.0
Brad Buchsbaum
mixeff: Audit-First Mixed-Effects Models via the 'mixeff-rs' Rust Crate
An R wrapper for the 'mixeff-rs' Rust crate, providing linear and generalized linear mixed-effects model fitting via lme4-style formulas. The wrapper is audit-first: every printed claim traces back to a versioned JSON artifact produced by the Rust compiler, and the package refuses to fabricate inference results that the engine cannot certify. See the package vignettes for migration from 'lme4' and the demystification surface for random-effects syntax.
Authors:
mixeff_0.2.0.tar.gz
mixeff_0.2.0.zip(r-4.7)mixeff_0.2.0.zip(r-4.6)mixeff_0.2.0.zip(r-4.5)
mixeff_0.2.0.tgz(r-4.6-x86_64)mixeff_0.2.0.tgz(r-4.6-arm64)mixeff_0.2.0.tgz(r-4.5-x86_64)mixeff_0.2.0.tgz(r-4.5-arm64)
mixeff_0.2.0.tar.gz(r-4.7-arm64)mixeff_0.2.0.tar.gz(r-4.7-x86_64)mixeff_0.2.0.tar.gz(r-4.6-arm64)mixeff_0.2.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mixeff/json (API)
| # Install 'mixeff' in R: |
| install.packages('mixeff', repos = c('https://bbuchsbaum.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bbuchsbaum/mixeff/issues
Pkgdown/docs site:https://bbuchsbaum.github.io
Last updated from:fb76713b0b. Checks:11 OK, 1 ERROR, 1 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 475 | ||
| linux-devel-x86_64 | OK | 503 | ||
| source / vignettes | OK | 543 | ||
| linux-release-arm64 | OK | 468 | ||
| linux-release-x86_64 | OK | 401 | ||
| macos-release-arm64 | OK | 500 | ||
| macos-release-x86_64 | OK | 1089 | ||
| macos-oldrel-arm64 | OK | 431 | ||
| macos-oldrel-x86_64 | OK | 777 | ||
| windows-devel | ERROR | 523 | ||
| windows-release | OK | 674 | ||
| windows-oldrel | OK | 638 | ||
| wasm-release | FAIL | 308 |
Exports:as_jsonauditaudit_designbootstrap_controlchangescomparecompare_covariancecompile_modelcontrastdf_for_contrastdiagnosticsemm_basis.mm_glmmemm_basis.mm_lmmestimabilityexplain_modelfit_handle_alivefit_statusfixefgetMEglmminference_optionsinference_tableis_singularlmmmm_comparisonsmm_controlmm_formula_manifestmm_gridmm_json_known_schemasmm_json_negotiatemm_lincombmm_meansmm_negative_binomialmm_parse_formulamm_predictionsmodel_reportngrpsoptimizer_certificateparameterizationparametric_bootstraprandom_blocksrandom_optionsranefrecover_data.mm_glmmrecover_data.mm_lmmrefitreporting_tablereproducibilityreviverolestest_effecttest_random_effectVarCorrverify_convergence
Inference Where Standard Mixed-Model p-values Break Down
Last update: 2026-07-10
Started: 2026-05-17
Introduction to mixeff
What problem does it solve? | One small model | Reading the formula before fitting | Reporting tables | Saving and reloading | Lower-level tools | What's next?
Last update: 2026-07-10
Started: 2026-05-17
Marginal Means and Comparisons
The study | Fit the model | Reference grids with mm_grid() | Cell predictions with mm_predictions() | Marginal means with mm_means() | Pairwise comparisons with mm_comparisons() | Conditional comparisons with by = | Constraining the grid with at = | Custom contrasts with mm_lincomb() | The emmeans bridge | Reading status and reason | Where to read next
Last update: 2026-07-10
Started: 2026-07-03
Migrating from lme4
The two edits | Verb map | Argument map for lmm() / glmm() | Four things that will bite, and the fix | What is NA-with-a-reason (and why)
Last update: 2026-07-10
Started: 2026-06-02
Reporting Linear Mixed Models
What model will we report? | What did the formula request? | What fit was used? | Which design facts belong in the report? | How are estimates and p-values labelled? | How are random effects reported? | What is unavailable or caveated? | What should go into your written report?
Last update: 2026-07-10
Started: 2026-05-17
Reproducing the Loo Aphantasia GLMMs
Inferential surfaces | Out of scope here | Caveats | Citation
Last update: 2026-07-10
Started: 2026-05-21
Your First Mixed Model with mixeff
The data | Step 1: Compile the model | Step 2: Fit | Step 3: Read the summary | Step 4: Extract components | Step 5: Test a specific claim | Step 6: Compare specific conditions | Step 7: Save and reload | Where to go next
Last update: 2026-07-10
Started: 2026-07-03
GLMM Fitting and Model Comparison
Family and Audit | Fit | Quadrature Sensitivity | Current Boundaries
Last update: 2026-07-03
Started: 2026-05-17
Demystifying Random-Effects Formulas
What does (1 | subject) say? | What changes when you add a random slope? | What do split blocks and || mean? | What are the three kinds of help? | How do you inspect nearby formulas? | Why is there no recommendation row? | Where do fitted-model changes appear?
Last update: 2026-06-11
Started: 2026-05-17
Inference You Can Report
What model are we fitting? | Coefficient p-values | Contrasts | Term tests | Model comparisons | Unavailable is still useful information
Last update: 2026-06-09
Started: 2026-05-17
Why mixeff?
The dataset | A. The formula stays familiar | B. When a fit is degenerate, you find out which part | C. Expose when asymptotics are weak, then offer bootstrap | D. The fit is the record | What this page did not show | Where to read next
Last update: 2026-06-02
Started: 2026-05-17
Benchmarking mixeff
What does the benchmark show? | What should you measure? | How do you benchmark fitting? | How do you benchmark bootstrap? | What does inference method choice cost? | How do you read the result? | What should go in a report?
Last update: 2026-05-31
Started: 2026-05-17
Inference Method Glossary
expected_status | expected_reliability_reason | reason_code
Last update: 2026-05-31
Started: 2026-05-31
Saving and Reloading Fits
Fit a model | Round trip through RDS | Rebuild design matrices when needed | What stays explicit? | What should you report?
Last update: 2026-05-31
Started: 2026-05-17
Fitting Linear Mixed Models
What data are we fitting? | What happens when you call lmm()? | How do you read the coefficient table? | Which familiar extractors work? | How do prediction and residuals line up? | Where is the design audit? | What should you read next?
Last update: 2026-05-17
Started: 2026-05-17
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Analysis of deviance for GLMMs | anova.mm_glmm |
| Serialize a mixeff spec or fit to JSON | as_json as_json.mm_compiled |
| Audit a compiled model spec or fitted model | audit audit.default audit.mm_compiled |
| Deprecated alias for 'audit()' | audit_design |
| Fixed-effect bootstrap control | bootstrap_control |
| Show requested, effective, and fitted model-state changes | changes changes.mm_compiled |
| Compare fitted mixeff models | compare compare.mm_lmm |
| Compare covariance parameterizations for current random terms | compare_covariance |
| Compile a mixed-effects model spec without fitting | compile_model |
| Confidence intervals for fixed effects of a mixeff GLMM | confint.mm_glmm |
| Contrast fixed effects | contrast contrast.mm_glmm contrast.mm_lmm |
| Degrees of freedom for a contrast | df_for_contrast df_for_contrast.mm_lmm |
| Inspect mixeff diagnostics and fit status | diagnostics diagnostics.mm_compiled fit_status fit_status.mm_compiled fit_status.mm_fit |
| Drop one fixed-effect term at a time from a GLMM | drop1.mm_glmm |
| Drop one fixed-effect term at a time | drop1.mm_lmm |
| Assess contrast estimability | estimability estimability.mm_lmm |
| Explain the random-effects structure of a compiled model | explain_model |
| Test whether a mixeff fit has a live native handle | fit_handle_alive fit_handle_alive.mm_fit |
| Extract low-level model components | getME getME.mm_lmm |
| Fit a generalized linear mixed model | glmm |
| Inspect inference methods available for this fit | inference_options inference_options.mm_lmm |
| Fixed-effect inference table | inference_table inference_table.mm_lmm |
| Test whether a fit is singular or reduced-rank | is_singular is_singular.mm_lmm |
| Fit a linear mixed-effects model | lmm |
| Control mixeff fitting behavior | mm_control |
| The wrapper's formula manifest | mm_formula_manifest |
| Marginal grids, predictions, means, and comparisons | mm_comparisons mm_comparisons.mm_lmm mm_grid mm_grid.mm_lmm mm_means mm_means.mm_lmm mm_predictions mm_predictions.mm_lmm |
| Closed list of schema/version pairs the wrapper understands | mm_json_known_schemas |
| Negotiate a JSON schema header against what 'mixeff' supports | mm_json_negotiate |
| Wald inference on a linear combination of fixed effects | mm_lincomb mm_lincomb.default mm_lincomb.mm_glmm mm_lincomb.mm_lmm |
| Extract components from a fitted mixeff LMM | AIC.mm_glmm AIC.mm_lmm as.data.frame.mm_ranef as.data.frame.mm_varcorr BIC.mm_glmm BIC.mm_lmm coef.mm_glmm coef.mm_lmm deviance.mm_glmm deviance.mm_lmm df.residual.mm_glmm df.residual.mm_lmm extractAIC.mm_glmm extractAIC.mm_lmm fixef fixef.mm_glmm fixef.mm_lmm formula.mm_glmm formula.mm_lmm logLik.mm_glmm logLik.mm_lmm mm_lmm-methods model.frame.mm_glmm model.frame.mm_lmm model.matrix.mm_glmm model.matrix.mm_lmm ngrps ngrps.default ngrps.mm_glmm ngrps.mm_lmm nobs.mm_glmm nobs.mm_lmm ranef ranef.mm_glmm ranef.mm_lmm sigma.mm_glmm sigma.mm_lmm terms.mm_glmm terms.mm_lmm VarCorr VarCorr.mm_glmm VarCorr.mm_lmm vcov.mm_glmm vcov.mm_lmm weights.mm_glmm weights.mm_lmm |
| Negative-binomial family for 'glmm()' | mm_negative_binomial |
| Parse and canonicalize an lme4-style formula | mm_parse_formula |
| Produce reporting tables for a fitted mixeff model | model_report model_report.mm_fit reporting_table reporting_table.mm_drop1 reporting_table.mm_fit reporting_table.mm_model_comparison reporting_table.mm_random_effect_test |
| Inspect the optimizer certificate | optimizer_certificate optimizer_certificate.mm_compiled |
| Inspect covariance parameterization | parameterization parameterization.mm_compiled |
| Parametric bootstrap likelihood-ratio comparison | parametric_bootstrap |
| Predict from a fitted mixeff GLMM | predict.mm_glmm |
| Predict from a fitted mixeff LMM | fitted.mm_glmm fitted.mm_lmm predict.mm_lmm residuals.mm_glmm residuals.mm_lmm |
| Profile a fitted linear mixed model | profile.mm_lmm |
| Inspect random-effect blocks | random_blocks random_blocks.mm_compiled |
| Inspect nearby random-effect spellings for one grouping factor | random_options |
| Refit a mixeff LMM with a new response | refit refit.mm_lmm |
| Inspect reproducibility metadata | reproducibility reproducibility.mm_compiled |
| Revive a serialized mixeff object | revive revive.mm_fit |
| Declare or inspect design roles | roles |
| Simulate from a mixeff LMM | simulate.mm_lmm |
| Test a fixed-effect term | test_effect test_effect.mm_lmm |
| Test a random-effect variance component | test_random_effect test_random_effect.mm_lmm |
| Update and re-fit a mixeff model | update.mm update.mm_glmm update.mm_lmm |
| Verify convergence of a fitted linear mixed model | verify_convergence verify_convergence.default verify_convergence.mm_lmm |