A three-step approach is proposed to estimate latent Markov (LM) models for longitudinal data with and without covariates. The approach is based on a preliminary clustering of sample units on the basis of time-specific responses only, and is particularly useful when a large number of response...

As an important extension of the regular kappa statistic, the weighted kappa statistic has been widely used to assess the agreement between two procedures for independent matched-pair ordinal data. For clustered matched-pair ordinal data, based on the delta method and sampling techniques, a...

Extraction of curvilinear structures from noisy data is an essential task in many application fields such as data analysis, pattern recognition and machine vision. The proposed approach assumes a random process in which the samples are obtained from a generative model. The model specifies a set...

Variance components (VC) and generalized estimating equations (GEE) are two approaches for estimating concordance correlation coefficients (CCC) adjusting for covariates, and allowing dependency between replicated samples. However, under VC and GEE, a model including all potential explanatory...

In medicine, it is often useful to stratify patients according to disease risk, severity, or response to therapy. Since many diseases arise from complex gene–gene and gene–environment interactions, patient strata may be defined by combinations of genetic and environmental factors....

Scan statistics have been widely applied to test for unusual cluster of events in many scientific areas. It has been of practical interest on how to select the window size of a scan statistic. An adaptive procedure for multiple window scan statistics is proposed and the distributions are studied...

Ensemble pruning deals with the selection of base learners prior to combination in order to improve prediction accuracy and efficiency. In the ensemble literature, it has been pointed out that in order for an ensemble classifier to achieve higher prediction accuracy, it is critical for the...

Record data are commonly seen in everyday life, e.g., concentration of emerging contaminants in environmental studies. Based on record data, this study investigates point estimation and confidence intervals estimation for the Weibull distribution. The uniformly minimum variance unbiased...

Estimating a covariance matrix is an important task in applications where the number of variables is larger than the number of observations. Shrinkage approaches for estimating a high-dimensional covariance matrix are often employed to circumvent the limitations of the sample covariance matrix....

A novel smoothed empirical likelihood (EL) approach that incorporates kernel estimation of the area under the receiver operating characteristic curve (AUC) to construct nonparametric confidence intervals of AUC based on the best linear combination (BLC) of biomarkers is proposed. The method has...