Family and Audit | Fit | The fast profiled path | Prediction | Quadrature Sensitivity | What is refused where
Package: mixeff 0.2.0
mixeff: Mixed-Effects Models via the 'mixeff-rs' Rust Crate
Fits linear and generalized linear mixed-effects models from 'lme4'-style formulas, with optimization by the bundled 'mixeff-rs' Rust crate. A fitted model stores the compiled model specification, the optimizer certificate, and per-coefficient inference metadata (method, status, reliability) as data, so a result can be inspected, saved, and reloaded without a live handle to the compiled engine. When an inference method is unavailable for a fit, the affected value is either withheld with a stable reason code or reported under the name of the method actually used, never silently swapped. Vignettes cover migration from 'lme4' and the meaning of random-effects formula syntax.
Authors:
mixeff_0.2.0.tar.gz
mixeff_0.2.0.zip(r-4.7-x86_64)mixeff_0.2.0.zip(r-4.7-arm64)mixeff_0.2.0.zip(r-4.6-x86_64)mixeff_0.2.0.zip(r-4.6-arm64)mixeff_0.2.0.zip(r-4.5-x86_64)
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:6e9a62a53f. Checks:14 OK, 1 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 476 | ||
| linux-devel-x86_64 | OK | 500 | ||
| source / vignettes | OK | 565 | ||
| linux-release-arm64 | OK | 431 | ||
| linux-release-x86_64 | OK | 516 | ||
| macos-release-arm64 | OK | 538 | ||
| macos-release-x86_64 | OK | 1086 | ||
| macos-oldrel-arm64 | OK | 419 | ||
| macos-oldrel-x86_64 | OK | 886 | ||
| windows-devel-arm64 | OK | 718 | ||
| windows-devel-x86_64 | OK | 893 | ||
| windows-release-arm64 | OK | 832 | ||
| windows-release-x86_64 | OK | 551 | ||
| windows-oldrel-x86_64 | OK | 941 | ||
| wasm-release | FAIL | 131 |
Exports:as_jsonauditaudit_designbootstrap_controlchangescomparecompare_covariancecompile_modelcontrastdf_for_contrastdiagnosticsemm_basis.mm_glmmemm_basis.mm_lmmestimabilityexplain_modelfit_handle_alivefit_statusfixefgetMEglmminference_optionsinference_tableis_singularlmmmm_allfitmm_bootmermm_comparisonsmm_controlmm_formula_manifestmm_gridmm_iccmm_json_known_schemasmm_json_negotiatemm_lincombmm_lmlistmm_meansmm_negative_binomialmm_parse_formulamm_predictionsmm_r2mm_variance_componentsmodel_reportngrpsoptimizer_certificateparameterizationparametric_bootstraprandom_blocksrandom_optionsranefrecover_data.mm_glmmrecover_data.mm_lmmrefitREMLcritrePCAreporting_tablereproducibilityreviverolesstepsupported_modelstest_effecttest_random_effectVarCorrverify_convergence
Generalized Linear Mixed Models
Last update: 2026-10-10
Started: 2026-05-17
Inference
What model are we fitting? | Coefficient p-values | Contrasts | Term tests | Model comparisons | When standard p-values are not well justified | The route map | How do I test the term anyway? | What about confidence intervals? | Where does cluster bootstrap stand? | Variance-component boundary tests | Profile confidence intervals | GLMM inference: the three-route contract | Estimands: what are you averaging? | The study | 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 covariance contract | Summary | References
Last update: 2026-10-10
Started: 2026-05-17
Introduction and the Supported Model Contract
The dataset | A. The formula stays familiar | B. When a fit is degenerate, the object says so | C. Inference labels its method | The supported model contract | D. The fit is the record | Saving, reloading, and reviving in practice | The artifact contract | Lower-level tools | Where to read next
Last update: 2026-10-10
Started: 2026-05-17
Linear Mixed Models
The data | Step 1: Read the formula before you fit | Step 2: Fit | Step 3: Read the summary | Step 4: Extract components | Step 5: Prediction and residuals | Prediction standard errors and intervals | Step 6: Case weights | Random-effects formulas in depth | What does (1 | subject) say? | What changes when you add a random slope? | What do split blocks and || mean? | Nested and crossed grouping | 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? | Where to go next
Last update: 2026-10-10
Started: 2026-08-02
Migrating from lme4
The two edits | Verb map | Argument map for lmm() / glmm() | Four differences to check when porting | The supported envelope, generated | What is NA-with-a-reason (and why)
Last update: 2026-10-10
Started: 2026-06-02
Convergence, Boundaries, and Singularity
What converged_interior establishes — and what it does not | Boundary and reduced-rank fits are labeled facts | How singularity is decided: rank, not θ entries | Verifying an optimum: verify_convergence() | When the requested estimator does not certify (GLMM) | What a boundary refuses | References
Last update: 2026-08-02
Started: 2026-08-02
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Analysis of deviance for GLMMs | anova.mm_glmm |
| Analysis of variance for a mixeff LMM | anova.mm_lmm |
| 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 |
| Confidence intervals for a mixeff LMM | confint.mm_lmm |
| 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_glmm getME.mm_lmm |
| Fit a generalized linear mixed model | glmm |
| Inspect inference methods available for this fit | inference_options inference_options.mm_glmm inference_options.mm_lmm |
| Fixed-effect inference table | inference_table inference_table.mm_glmm inference_table.mm_lmm |
| Test whether a fit is singular or reduced-rank | is_singular is_singular.mm_glmm is_singular.mm_lmm |
| Fit a linear mixed-effects model | lmm |
| Refit a model with every available optimizer | mm_allfit |
| Parametric bootstrap of any statistic of a fitted LMM | mm_bootmer |
| Control mixeff fitting behavior | mm_control |
| Family objects and prior weights for mixeff fits | family.mm_glmm family.mm_lmm mm_family weights.mm_glmm weights.mm_lmm |
| 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 |
| Leverage, Cook's distance and deletion influence for mixeff fits | cooks.distance.mm_glmm cooks.distance.mm_influence cooks.distance.mm_lmm dfbeta.mm_influence dfbetas.mm_influence hatvalues.mm_glmm hatvalues.mm_lmm influence.mm_glmm influence.mm_lmm mm_influence |
| 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 |
| Per-group linear (or generalized linear) model fits | mm_lmlist |
| 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.default 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.default ranef.mm_glmm ranef.mm_lmm sigma.mm_glmm sigma.mm_lmm terms.mm_glmm terms.mm_lmm VarCorr VarCorr.default VarCorr.mm_glmm VarCorr.mm_lmm vcov.mm_glmm vcov.mm_lmm |
| Negative-binomial family for 'glmm()' | mm_negative_binomial |
| Parse and canonicalize an lme4-style formula | mm_parse_formula |
| Variance decomposition, Nakagawa R2 and ICC for mixeff fits | mm_icc mm_r2 mm_variance_components |
| 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 |
| Diagnostic plots for mixeff fits | plot.mm_fit plot.mm_glmm plot.mm_lmm qqnorm.mm_glmm qqnorm.mm_lmm |
| Caterpillar and Q-Q plots of random effects | plot.mm_ranef qqnorm.mm_ranef |
| 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 model with a new response | refit refit.default refit.mm_glmm refit.mm_lmm |
| REML criterion of a linear mixed model | REMLcrit |
| PCA of the random-effects covariance (lme4's 'rePCA()') | rePCA rePCA.default rePCA.mm_glmm rePCA.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 responses from a mixeff fit | simulate.mm_glmm simulate.mm_lmm |
| Stepwise model selection | step step.default |
| Backward elimination of random and fixed effects (lmerTest's 'step()') | step.mm_lmm |
| The supported model envelope | supported_models |
| 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 mixed model | verify_convergence verify_convergence.default verify_convergence.mm_glmm verify_convergence.mm_lmm |