brglm2 (version 0.6.2)

mis: A link-glm object for misclassified responses in binomial regression models

Description

mis is a link-glm object that specifies the link function in Neuhaus (1999, expression~(8)) for handling misclassified responses in binomial regression models using maximum likelihood. A prior specification of the sensitivity and specificity is required.

Usage

mis(link = "logit", sensitivity = 1, specificity = 1)

Arguments

link

the baseline link to be used.

sensitivity

the probability of observing a success given that a success actually took place given any covariate values.

specificity

the probability of observing a failure given that a failure actually took place given any covariate values.

Details

sensitivity + specificity should be greater or equal to 1, otherwise it is implied that the procedure producing the responses performs worse than chance in terms of misclassification.

References

Neuhaus J. M. (1999). Bias and efficiency loss due to misclassified responses in binary regression. Biometrika, **86**, 843-855

See Also

glm, brglm_fit

Examples

# NOT RUN {
## Define a few links with some misclassification
logit_mis <- mis(link = "logit", sensitivity = 0.9, specificity = 0.9)

lizards_f <- cbind(grahami, opalinus) ~ height + diameter + light + time

lizardsML <- glm(lizards_f, family = binomial(logit), data = lizards)

lizardsML_mis <- update(lizardsML, family = binomial(logit_mis),
                        start = coef(lizardsML))

## A notable change is coefficients is noted here compared to when
## specificity and sensitity are 1
coef(lizardsML)
coef(lizardsML_mis)

## Bias reduction is also possible
update(lizardsML_mis, method = "brglmFit", type = "AS_mean",
       start = coef(lizardsML))

update(lizardsML_mis, method = "brglmFit", type = "AS_median",
       start = coef(lizardsML))

# }