Choice between Semi-parametric Estimators of Markov and Non-Markov Multi-state Models from Coarsened Observations

Abstract.  We consider models based on multivariate counting processes, including multi-state models. These models are specified semi-parametrically by a set of functions and real parameters. We consider inference for these models based on coarsened observations, focusing on families of smooth estimators such as produced by penalized likelihood. An important issue is the choice of model structure, for instance, the choice between a Markov and some non-Markov models. We define in a general context the expected Kullback–Leibler criterion and we show that the likelihood-based cross-validation (LCV) is a nearly unbiased estimator of it. We give a general form of an approximate of the leave-one-out LCV. The approach is studied by simulations, and it is illustrated by estimating a Markov and two semi-Markov illness–death models with application on dementia using data of a large cohort study.     

Career Planning in Prison: Ex-inmates Help Inmates

Corrections psychology has been called the “stepchild” of the field. Like the stepchild stereotype, it is neglected and ignored. (Wendt, 1979, p. 10)     

Children and Literature

Correspondence to Kate Wilson, Senior Lecturer, Department of Social Policy and Social Work, University of York, Heslington, York YO1 5DD Summary The paper draws on a range of fictional and autobiographicalaccounts of childhood to illustrate different aspects of children'sperceptions and responses and to show how they can enhance theadult's ability to understand what a child is experiencing.Three themes, concerning children's perceptions and suggestibility,their sense of helplessness and difficulty in communicatingwith adults, and their responses to loss and change are illustratedthrough the work of nineteenth- and twentieth-century creativewriters. It is argued that literary accounts can work at a consciousand unconscious level in heightening our understanding, andmay also give us a perspective on how childhood experiencesinfluence the adult personality.     

Rating Methodological Quality: Toward Improved Assessment and Investigation

Assessing methodological quality is considered essential in deciding what investigations to include in research syntheses and in detecting potential sources of bias in meta-analytic results. Quality assessment is also useful in characterizing the strengths and limitations of the research in an area of study. Although numerous instruments to measure research quality have been developed, they have lacked empirically-supported components. In addition, different summary quality scales have yielded different findings when they were used to weight treatment effect estimates for the same body of research. Suggestions for developing improved quality instruments include: distinguishing distinct domains of quality, such as internal validity, external validity, the completeness of the study report, and adherence to ethical practices; focusing on individual aspects, rather than domains of quality; and focusing on empirically-verified criteria. Other ways to facilitate the constructive use of quality assessment are to improve and standardize the reporting of research investigations, so that the quality of studies can be more equitably and thoroughly compared, and to identify optimal methods for incorporating study quality ratings into meta-analyses.