New functionality brnb() allows fitting negative binomial regression models using implicit and explicit bias reduction methods. See vignettes for a case study. simulate() method for objects of class brmultinom and bracl ordinal_superiority() method to estimate Agresti and Kateri (2017)'s ordinal superiority measures, and compute bias corrections for those. Bug fixes Fixed a bug that would return an error when Wald.ratios = TRUE in summary.brmultinom. Fixed bug in vcov.bracl that would return an error if the "bracl" object was computed using bracl() with parallel = TRUE and one covariate. Fixed a bug in bracl() related to the handling or zero weights that could result in hard-to-traceback errors. Fixed a bug in bracl() that could cause er...
<p><i>Note</i>: Negative binomial regressions (N = 153) of the number of reporting errors per paper ...
A substantial enhancement of the only text devoted entirely to the negative binomial model and its m...
Negative binomial regression results of models with different datasets and variables (standard error...
New functionality brnb() allows fitting negative binomial regression models using implicit and expl...
Fit binomial-response GLMs using either a modified-score approach to bias reduction or maximum penal...
Noteworthy changes include: substantial expansions to sections 10.3.1 (multinomial regression) an...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to...
Bug fixes print.brmultinom is now exported, so bracl and brmultinom fits print correctly New funct...
Bug fixes Fixed bug where confint() was not returning anything when applied to objects of class brm...
Noteworthy changes include: using the Metropolis algorithm to fit the bivariate Bernoulli model for...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small t...
brglm2 0.9.1 Other improvements, updates and additions Added the enzymes and hepatitis data sets (f...
brglm2 0.8.2 Other improvements, updates and additions Housekeeping. Removed lpSolveAPI from import...
Difference in AIC between null and alternative models using Poisson (black) and negative binomial (r...
Other improvements, updates and additions vcov.brglmFit objects now uses vcov.summary.glm and suppo...
<p><i>Note</i>: Negative binomial regressions (N = 153) of the number of reporting errors per paper ...
A substantial enhancement of the only text devoted entirely to the negative binomial model and its m...
Negative binomial regression results of models with different datasets and variables (standard error...
New functionality brnb() allows fitting negative binomial regression models using implicit and expl...
Fit binomial-response GLMs using either a modified-score approach to bias reduction or maximum penal...
Noteworthy changes include: substantial expansions to sections 10.3.1 (multinomial regression) an...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to...
Bug fixes print.brmultinom is now exported, so bracl and brmultinom fits print correctly New funct...
Bug fixes Fixed bug where confint() was not returning anything when applied to objects of class brm...
Noteworthy changes include: using the Metropolis algorithm to fit the bivariate Bernoulli model for...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small t...
brglm2 0.9.1 Other improvements, updates and additions Added the enzymes and hepatitis data sets (f...
brglm2 0.8.2 Other improvements, updates and additions Housekeeping. Removed lpSolveAPI from import...
Difference in AIC between null and alternative models using Poisson (black) and negative binomial (r...
Other improvements, updates and additions vcov.brglmFit objects now uses vcov.summary.glm and suppo...
<p><i>Note</i>: Negative binomial regressions (N = 153) of the number of reporting errors per paper ...
A substantial enhancement of the only text devoted entirely to the negative binomial model and its m...
Negative binomial regression results of models with different datasets and variables (standard error...