Bagging and random forests are widely used ensemble methods. Each forms an ensemble of models by randomly perturbing the fitting of a base learner. The standard errors estimation of the resultant regression function is considered. Three estimators are discussed. One, based on the jackknife, is...

The construction of a multivariate two sample test is considered. An attractive approach to this problem, for instance when the data contain missing values or the number of variables is large, is to form an overall test by combining the componentwise test statistics. This can be done via their...

The aim of this study was to examine the effect of family income on accessibility to dental services among adults in Norway. The analyses was performed on a set of national data collected in 1989, which was representative of the non-institutionalized Norwegian population aged 20 years and above....

This manual describes a Stata program gllamm that can estimate Generalized Linear Latent and Mixed Models (GLLAMMs). GLLAMMs are a class of multilevel latent variable models for (multivariate) responses of mixed type including continuous responses, counts, duration/survival data, dichotomous,...

Multilevel modelling is sometimes used for data from complex surveys involving multistage sampling, unequal sampling probabilities and stratification. We consider generalized linear mixed models and particularly the case of dichotomous responses. A pseudolikelihood approach for accommodating...