Predicted Values and Discrete Changes for GLM
Functions to calculate predicted values and the difference between the two cases with confidence interval for glm, glm.nb, polr and multinom.

Functions to calculate predicted values and the difference between
the two cases with confidence interval for glm(), glm.nb(), polr() and multinom().

2017-12-06 14:42:27 UTC; Benjamin Schlegel

2018-05-03 11:01:05 UTC; Benjamin Schlegel

Functions to calculate predicted values and the difference between
the two cases with confidence interval for lm() [linear model], glm() [general linear model], glm.nb() [negative binomial model],
polr() [ordinal logistic model] and multinom() [multinomial model] using Monte Carlo simulations. Reference: Bennet A. Zelner (2009) <doi:10.1002/smj.783>.
2019-09-04 11:56:49 UTC; Benjamin Schlegel

Functions to calculate predicted values and the difference between
the two cases with confidence interval for lm() [linear model], glm() [general linear model], glm.nb() [negative binomial model],
polr() [ordinal logistic model], multinom() [multinomial model] and tobit() [tobit model] using Monte Carlo simulations or bootstrap. Reference: Bennet A. Zelner (2009) <doi:10.1002/smj.783>.
knitr, rmarkdown, schlegel, ggplot2, devtools

Functions to calculate predicted values and the difference between
the two cases with confidence interval for lm() [linear model], glm() [generalised linear model], glm.nb() [negative binomial model],
polr() [ordinal logistic model], multinom() [multinomial model] and tobit() [tobit model],
svyglm() [survey-weighted generalised linear models] using Monte Carlo simulations or bootstrap. Reference: Bennet A. Zelner (2009) <doi:10.1002/smj.783>.
R (>= 3.5.0), stats, MASS, parallel, mlogit, dfidx, survey

Ian Marschner (using code from glm and glm.fit in the stats
package)
Fits generalized linear models using the same model
specification as glm in the stats package, but with a modified
default fitting method that provides greater stability for
models that may fail to converge using glm