Patient dropout is a common problem in studies that collect repeated binary measurements. Generalized estimating equations (GEE) are often used to analyze such data. The dropout mechanism may be plausibly missing at random (MAR), i.e. unrelated to future measurements given covariates and past...

The aim of this paper is to investigate the robustness properties of likelihood inference with respect to rounding effects. Attention is focused on exponential families and on inference about a scalar parameter of interest, also in the presence of nuisance parameters. A summary value of the...

Influence functions are commonly used as diagnostic tools in order to investigate sensitivity aspects in principal component analysis. This paper suggests a practical alternative for the eigenvalues by introducing a sensitivity measure derived from the classical Lorenz curve and associated Gini...

A controlled clinical trial was conducted to investigate the efficacy effect of a chemical compound in the treatment of Premenstrual Dysphoric Disorder (PMDD). The data from the trial showed a non-monotone pattern of missing data and an ante-dependence covariance structure. A new analytical...

Multiple imputation has emerged as a widely used model-based approach in dealing with incomplete data in many application areas. Gaussian and log-linear imputation models are fairly straightforward to implement for continuous and discrete data, respectively. However, in missing data settings...

The coefficient of determination, known also as the R2, is a common measure in regression analysis. Many scientists use the R2 and the adjusted R2 on a regular basis. In most cases, the researchers treat the coefficient of determination as an index of 'usefulness' or 'goodness of fit,' and in...

To allow more accurate prediction of hospital length of stay (LOS) after serious injury or illness, a multi-state model is proposed, in which transitions from the hospitalized state to three possible outcome states (home, long-term care, or death) are assumed to follow constant rates for each of...

Maximum likelihood estimation and goodness-of-fit techniques are used within a competing risks framework to obtain maximum likelihood estimates of hazard, density, and survivor functions for randomly right-censored variables. Goodness-of- fit techniques are used to fit distributions to the crude...

This article presents a continuous-time Bayesian model for analyzing durations of behavior displays in social interactions. Duration data of social interactions are often complex because of repeated behaviors (events) at individual or group (e.g. dyad) level, multiple behaviors (multistates),...

The cohort under study comprises A-bomb survivors residing in Hiroshima Prefecture since 1968. After this year, thousands of survivors were newly recognized every year. The aim of this study is to determine whether the survival experience of the late entrants to the cohort is significantly...