Helper functions that returns the results of stats::glm() when Poisson or Quasi-Poisson
distributions are needed (see family parameter), or MASS::glm.nb() for Negative Binomial
distributions. Link function for the GLM is log.
Usage
h_glm_count(.var, .df_row, variables, distribution, weights)
h_glm_poisson(.var, .df_row, variables, weights)
h_glm_quasipoisson(.var, .df_row, variables, weights)
h_glm_negbin(.var, .df_row, variables, weights)Arguments
- .var
(
string)
single variable name that is passed byrtableswhen requested by a statistics function.- .df_row
(
data.frame)
dataset that includes all the variables that are called in.varandvariables.- variables
-
(named
listofstring)
list of additional analysis variables, with expected elements:arm(string)
group variable, for which the covariate adjusted means of multiple groups will be summarized. Specifically, the first level ofarmvariable is taken as the reference group.covariates(character)
a vector that can contain single variable names (such as"X1"), and/or interaction terms indicated by"X1 * X2".offset(numeric)
a numeric vector or scalar adding an offset.
- distribution
(
character)
a character value specifying the distribution used in the regression (Poisson, Quasi-Poisson, negative binomial).- weights
(
character)
a character vector specifying weights used in averaging predictions. Number of weights must equal the number of levels included in the covariates. Weights option passed toemmeans::emmeans().
Value
h_glm_count()returns the results of the selected model.
h_glm_poisson()returns the results of a Poisson model.
h_glm_quasipoisson()returns the results of a Quasi-Poisson model.
h_glm_negbin()returns the results of a negative binomial model.
Functions
h_glm_count(): Helper function to return the results of the selected model (Poisson, Quasi-Poisson, negative binomial).h_glm_poisson(): Helper function to return results of a Poisson model.h_glm_quasipoisson(): Helper function to return results of a Quasi-Poisson model.h_glm_negbin(): Helper function to return results of a negative binomial model.
