tidy.cmp: Tidy a(n) CMP model object

In mpcmp: Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression

Description

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

## S3 method for class 'cmp'
tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)

Arguments

x	an object class 'cmp' object, obtained from a call to glm.cmp
conf.int	Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.
conf.level	The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
exponentiate	Logical indicating whether or not to exponentiate the the coefficient estimates.
...	other arguments passed to or from other methods (currently unused).

Value

A tibble::tibble() with columns:

term	The name of the regression term.
estimate	The estimated value of the regression term.
std.error	The standard error of the regression term.
statistic	The value of a test statistic to use in a hypothesis that the regression term is non-zero.
p.value	The two-sided p-value associated with the observed statistic based on asymptotic normality.
parameter	Only for varying dispersion models. Type of coefficient being estimated: 'mu', 'nu'
conf.low	Lower bound on the confidence interval for the estimate.
conf.high	Upper bound on the confidence interval for the estimate.

Examples

data(attendance)
M.attendance <- glm.cmp(daysabs~ gender+math+prog, data=attendance)
tidy(M.attendance)

mpcmp documentation built on Oct. 26, 2020, 9:07 a.m.