In this article, we study a new linear discriminant function for three-level m-variate observations under the assumption of multivariate normality. We assume that the m-variate observations have a doubly exchangeable covariance structure consisting of three unstructured covariance matrices for...

Let T1 and T2 be the survival times of patients randomized to, respectively, two treatment groups. The probability P(T1T2) may be used as a measure on the effect of treatments in a randomized clinical trial. With potentially censored data observed and assuming that the density functions of...

In analyzing correlated data or clustered data with linear or logistic mixed effects model, one commonly assumes that the random effects follow a normal distribution with mean zero. However, this assumption might not be appropriate in many cases. In particular, substantial violation of normality...

Nonparametric inferential methods are discussed for the situation of multiple independent doubly Type-II censored samples. The basic distribution theory for the pooled sample is given assuming that the underlying distribution is continuous and it is demonstrated how the weights in the mixture...

Missing data are common wherever statistical methods are applied in practice. They present a problem in that they require that additional assumptions be made about the mechanism leading to the incompleteness of the data. By incorporating two models for the missing data process, doubly robust...

Testing the parametric distribution of a random variable is a fundamental problem in exploratory and inferential statistics. Classical empirical distribution function based goodness-of-fit tests typically require the data to be an independent and identically distributed realization of a certain...

We consider the problem of selecting grouped variables in linear regression and generalized linear regression models, based on penalized likelihood. A number of penalty functions have been used for this purpose, including the smoothly clipped absolute deviation (SCAD) penalty and the minimax...

Two connected extensions of the Fay–Herriot small area level model that are of practical and theoretical interest are proposed. The first extension allows for the sampling error to be non-symmetrically distributed. This is important for cases in which the sample sizes in the areas are not...

Agreement is a broad term simultaneously covering evaluations of accuracy and precision of measurements. Assessment of observer agreement is based on the similarity between readings made on the same subject by different observers. The assessment of agreement on categorical observations is...

Assuming homogeneous variance in a normal regression model is not always appropriate as invalid standard inference procedures may result from the improper estimation of the standard error when the disturbance process in a regression model presents heteroscedasticity. When both outliers and...