cmultinom: Fit Multinomial Log-linear Models with standard errors...

In rferrali/rogali: A series of functions for the corrupt_audit project

Description

Fit Multinomial Log-linear Models with standard errors clustered at municipality level

Usage

cmultinom(formula, data, formulaMatch = NULL, dataMatch = NULL,
  munCol = j, yearCol = year, stateCol = state, treatCol = treat,
  pool = T, nSamples = NULL, parallel = F, seed = NULL,
  cl = NULL, ...)

Arguments

formula	a formula expression as for regression models, of pooled form cbind(y1, y2, y3) ~ .
data	a data.frame in which to interpret the variables occurring in formula
formulaMatch	a formula used to compute propensity scores. Leave NULL if you don't want to use matching.
dataMatch	a data.frame used for matching; must contain all corrupt/innocent municipalities.
munCol	column in data and dataMatch (if doing matching) containing the municipality id, syntax as in dplyr
yearCol	column in data containing the year, syntax as in dplyr
stateCol	column in data containing the state, syntax as in dplyr
treatCol	column in dataMatch containing treatment status, syntax as in dplyr
pool	should data be pooled automatically?
nSamples	number of bootstrap replicates. If NULL, uses analytical standard errors instead
parallel	should the bootstrap be parallelized? if TRUE, the cl argument shoud not be NULL
seed	optional seed
cl	cluster used for parallelization
...	additional parameters passed on to multinom

Details

Make sure to check the cmultinommethods man page to see related methods. Also, check the riskCurve man page to compute a parametric risk curve.

rferrali/rogali documentation built on May 26, 2019, 7 p.m.