In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrik...

Abstract Background Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be smoothing by considering the knot coefficients from a regression spline as random effects. The resulting are called semiparametric (SPMMs). Allowing to follow normal distribution with mean zero and constant variance is equivalent using penalized ridge type penalty. We introduce...