mfx: negbinirr – R documentation

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mfx

negbinirr

Incidence rate ratios for a negative binomial regression.

Description

This function estimates a negative binomial regression model and calculates the corresponding incidence rate ratios.

Usage

negbinirr(formula, data, robust = FALSE, clustervar1 = NULL, 
          clustervar2 = NULL, start = NULL, control = glm.control())

Arguments

`formula`	an object of class “formula” (or one that can be coerced to that class).
`data`	the data frame containing these data. This argument must be used.
`robust`	if `TRUE` the function reports White/robust standard errors.
`clustervar1`	a character value naming the first cluster on which to adjust the standard errors.
`clustervar2`	a character value naming the second cluster on which to adjust the standard errors for two-way clustering.
`start`	starting values for the parameters in the `glm.nb` model.
`control`	see `glm.control`.

Details

If both robust=TRUE and !is.null(clustervar1) the function overrides the robust command and computes clustered standard errors.

Value

`irr`	a coefficient matrix with columns containing the estimates, associated standard errors, test statistics and p-values.
`fit`	the fitted `glm.nb` object.
`call`	the matched call.

Examples

# simulate some data
set.seed(12345)
n = 1000
x = rnorm(n)
y = rnegbin(n, mu = exp(1 + 0.5 * x), theta = 0.5)

data = data.frame(y,x)

negbinirr(formula=y~x,data=data)

mfx

Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs

v1.2-2

GPL-2 | GPL-3

Authors

Alan Fernihough [aut, cre], Arne Henningsen [ctb]

Initial release

2019-02-06