mis {brglm2} | R Documentation |
link-glm
object for misclassified responses in binomial regression modelsmis
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.
mis(link = "logit", sensitivity = 1, specificity = 1)
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. |
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.
Neuhaus J M (1999). Bias and efficiency loss due to misclassified responses in binary regression. Biometrika, **86**, 843-855 https://www.jstor.org/stable/2673589
## 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))