Joint modeling of longitudinal measurements and survival time has an important role in
analyzing medical data sets. For example, in HIV data sets, a biological marker such as CD4 …

In this paper, a joint model for analyzing multivariate mixed ordinal and continuous
responses, where continuous outcomes may be skew, is presented. For modeling the …

Multiple responses of mixed types are naturally encountered in a variety of data analysis
problems, which should be jointly analysed to achieve higher efficiency gains. As an efficient …

For the analysis of square contingency tables with ordinal categories, Tahata, Yamamoto
and Tomizawa (2009) considered the normal distribution type symmetry model, which may …

Motivated by the China Health and Nutrition Survey (CHNS) data, a semiparametric latent
variable model with a Dirichlet process (DP) mixtures prior on the latent variable is proposed …

In this article, an ECM algorithm is developed to obtain the maximum likelihood estimates of
parameters where multivariate skew-normal distribution is used for analyzing longitudinal …

In this paper an algorithm called SEM, which is a stochastic version of the EM algorithm, is
used to analyze multivariate skew-normal data with intermittent missing values. Also, a …

In this paper, a linear mixed effects model is used to fit skewed longitudinal data in the
presence of dropout. Two distributional assumptions are considered to produce background …

In this paper, multivariate skew-normal distribution is employed for analyzing an outcome
based dropout model for repeated measurements with non-random dropout in skew …

When the nature of a data set comes from a skew distribution, the use of usual Gaussian
mixed effect model can be unreliable. In recent years, skew-normal mixed effect models …