Description Details Author(s) References Examples

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.

The DESCRIPTION file:
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Haiyan Liu and Zhiyong Zhang

Maintainer: Zhiyong Zhang <[email protected]>

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

1 2 3 4 | ```
data(nlsy)
x=nlsy[, -1]
y=nlsy[,1]
mod=logistic4p(x, y, model='fn')
``` |

logistic4p documentation built on May 31, 2017, 4:24 a.m.

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