Package: betaregscale 2.6.9

José Evandeilton Lopes

betaregscale: Beta Regression for Interval-Censored Scale-Derived Outcomes

Maximum-likelihood estimation of beta regression models for responses derived from bounded rating scales. Observations are treated as interval-censored on (0, 1) after a scale-to-unit transformation, and the likelihood is built from the difference of the beta CDF at the interval endpoints. The complete likelihood supports mixed censoring types: uncensored, left-censored, right-censored, and interval-censored observations. Both fixed- and variable-dispersion submodels are supported, with flexible link functions for the mean and precision components. A compiled C++ backend (via 'Rcpp' and 'RcppArmadillo') provides numerically stable, high-performance log-likelihood evaluation. Standard S3 methods (print(), summary(), coef(), fitted(), residuals(), predict(), plot(), confint(), vcov(), logLik(), AIC(), BIC()) are available for fitted objects.

Authors:José Evandeilton Lopes [aut, cre], Wagner Hugo Bonat [aut]

betaregscale_2.6.9.tar.gz
betaregscale_2.6.9.tar.gz(r-4.7-arm64)betaregscale_2.6.9.tar.gz(r-4.7-x86_64)betaregscale_2.6.9.tar.gz(r-4.6-arm64)betaregscale_2.6.9.tar.gz(r-4.6-x86_64)
betaregscale_2.6.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
betaregscale/json (API)
NEWS

# Install 'betaregscale' in R:
install.packages('betaregscale', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/evandeilton/betaregscale/issues

Pkgdown/docs site:https://evandeilton.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

3.38 score 12 scripts 184 downloads 24 exports 22 dependencies

Last updated from:6fc0dec1ef. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK171
linux-devel-x86_64OK177
source / vignettesOK383
linux-release-arm64OK173
linux-release-x86_64OK176
wasm-releaseOK143

Exports:autoplot.brsautoplot.brs_bootstrapautoplot.brs_marginaleffectsautoplot.brsmmbrsbrs_bootstrapbrs_censbrs_checkbrs_coefbrs_cvbrs_estbrs_fit_fixedbrs_fit_varbrs_gofbrs_hessianbrs_marginaleffectsbrs_predict_scoreprobbrs_prepbrs_reparbrs_simbrs_tablebrsmmbrsmm_re_studyranef

Dependencies:clicpp11farverFormulaggplot2gluegtableisobandlabelinglifecyclenumDerivR6RColorBrewerRcppRcppArmadilloRcppEigenrlangS7scalesvctrsviridisLitewithr

Advanced Workflows for High-Level Users

Rendered frombrs-advanced-workflows.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-02-25
Started: 2026-02-25

Analyst Tools for betaregscale

Rendered frombrs-analyst-tools.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-02-25
Started: 2026-02-25

Introduction to betaregscale

Rendered frombrs-intro.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-02-25
Started: 2026-02-25

Mixed-Effects Beta Interval Regression with brsmm

Rendered frombrs-mm.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2026-02-25
Started: 2026-02-25

Readme and manuals

Help Manual

Help pageTopics
Akaike information criterionAIC.brs
AIC for brsmm modelsAIC.brsmm
Model comparison by analysis of deviance (LR test) for `brs`anova.brs
Model comparison by analysis of deviance (LR test) for `brsmm`anova.brsmm
ggplot2 autoplot for brs modelsautoplot.brs
ggplot2 autoplot for bootstrap resultsautoplot.brs_bootstrap
ggplot2 autoplot for marginal effectsautoplot.brs_marginaleffects
ggplot2 autoplot for brsmm modelsautoplot.brsmm
Bayesian information criterionBIC.brs
BIC for brsmm modelsBIC.brsmm
Fit a beta interval regression modelbrs
Parametric bootstrap confidence intervals for brs modelsbrs_bootstrap print.brs_bootstrap
Graphical and tabular censoring summarybrs_cens
Transform and validate a scale-derived response variablebrs_check
Internal coefficient table (deprecated, use brs_est() or summary())brs_coef
K-fold cross-validation for brs modelsbrs_cv
Coefficient estimates with inferencebrs_est
Goodness-of-fit measuresbrs_gof
Extract the Hessian matrixbrs_hessian
Marginal effects for brs modelsbrs_marginaleffects
Predict score probabilities from a fitted brs modelbrs_predict_scoreprob
Pre-process analyst data for beta interval regressionbrs_prep
Reparameterize (mu, phi) into beta shape parametersbrs_repar
Simulate data from beta interval modelsbrs_sim
Compare fitted brs models in a single tablebrs_table
Fit a mixed-effects beta interval regression modelbrsmm
Random-effects study for brsmm modelsbrsmm_re_study
Extract model coefficientscoef.brs
Extract coefficients from a brsmm fitcoef.brsmm
Wald confidence intervalsconfint.brs
Wald confidence intervals for brsmm modelsconfint.brsmm
Extract fitted valuesfitted.brs
Fitted values from a brsmm modelfitted.brsmm
Extract model formulaformula.brs
Extract model formulaformula.brsmm
Extract log-likelihoodlogLik.brs
Log-likelihood for brsmm modelslogLik.brsmm
Extract design matrixmodel.matrix.brs
Extract design matrixmodel.matrix.brsmm
Number of observationsnobs.brs
Number of observations in a brsmm fitnobs.brsmm
Diagnostic plots for beta interval regressionplot.brs
Diagnostic plots for mixed beta interval regressionplot.brsmm
Predict from a fitted modelpredict.brs
Predict from a brsmm modelpredict.brsmm
Print a fitted model (brief betareg style)print.brs
Print a fitted brsmm modelprint.brsmm
Print a random-effects studyprint.brsmm_re_study
Print a model summary (betareg style)print.summary.brs
Print summary for brsmm modelsprint.summary.brsmm
Extract random effectsranef
Extract random effects from a brsmm modelranef.brsmm
Extract residualsresiduals.brs
Residuals from a brsmm modelresiduals.brsmm
Summarize a fitted model (betareg style)summary.brs
Summarize a fitted brsmm modelsummary.brsmm
Variance-covariance matrix of estimated coefficientsvcov.brs
Variance-covariance matrix for brsmm coefficientsvcov.brsmm