mfx: logitor – R documentation

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mfx

logitor

Odds ratios for a logit regression.

Description

This function estimates a binary logistic regression model and calculates the corresponding odds ratios.

Usage

logitor(formula, data, robust = FALSE, clustervar1 = NULL, clustervar2 = NULL, 
        start = NULL, control = list())

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` 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

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

Examples

# simulate some data
set.seed(12345)
n = 1000
x = rnorm(n)

# binary outcome
y = ifelse(pnorm(1 + 0.5*x + rnorm(n))>0.5, 1, 0)

data = data.frame(y,x)
logitor(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