logistic4p-package: Logistic Regression with Misclassification in Dependent...

Description Details Author(s) References Examples

Description

Error in a binary dependent variable, also known as misclassification, has not drawn much attention in psychology. Ignoring misclassification in logistic regression can result in misleading parameter estimates and statistical inference. This package conducts logistic regression analysis with misspecification in outcome variables.

Details

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Author(s)

Haiyan Liu and Zhiyong Zhang

Maintainer: Zhiyong Zhang <johnnyzhz@gmail.com>

References

Liu, H. and Zhang, Z. (2016) Logistic Regression with Misclassification in Dependent Variables: Method and Software.(In preparation.)

Examples

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data(nlsy)
x=nlsy[, -1]
y=nlsy[,1]
mod=logistic4p(x, y, model='fn')

logistic4p documentation built on May 21, 2017, 3:32 a.m.

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