boot.misclassGLM: Compute Bootstrapped Standard Errors for 'misclassGLM' Fits
In misclassGLM: Computation of Generalized Linear Models with Misclassified Covariates Using Side Information

boot.misclassGLM

R Documentation

Compute Bootstrapped Standard Errors for `misclassGLM` Fits

Obtain bootstrapped standard errors.

boot.misclassGLM(ret, Y, X, Pmodel, PX, boot.fraction = 1, repetitions = 1000)

`ret`	a fitted object of class inheriting from 'misclassGLM'.
`Y`	a vector of integers or numerics. This is the dependent variable.
`X`	a matrix containing the independent variables.
`Pmodel`	a fitted model (e.g. of class 'GLM' or 'mlogit') to implicitly produce variations of the predicted true values probabilities. (Usually conditional on the observed misclassified values and additional covariates.)
`PX`	covariates matrix suitable for predicting probabilities from `Pmodel`, usually including the mismeasured covariate.
`boot.fraction`	fraction of sample to be used for estimating the bootstrapped standard errors, for speedup.
`repetitions`	number of bootstrap samples to be drown.