A modified random-effect procedure for combining risk difference in sets of 2×2 tables from clinical trials

Summary Meta-analyses of sets of clinical trials often combine risk differences from several 2×2 tables according to a random-effects model. The DerSimonian-Laird random-effects procedure, widely used for estimating the populaton mean risk difference, weights the risk difference from each primary study inversely proportional to an estimate of its variance (the sum of the between-study variance and the conditional within-study variance). Because those weights are not independent of the risk differences, however, the procedure sometimes exhibits bias and unnatural behavior. The present paper proposes a modified weighting scheme that uses the unconditional within-study variance to avoid this source of bias. The modified procedure has variance closer to that available from weighting by ideal weights when such weights are known. We studied the modified procedure in extensive simulation experiments using situations whose parameters resemble those of actual studies in medical research. For comparison we also included two unbiased procedures, the unweighted mean and a sample-size-weighted mean; their relative variability depends on the extent of heterogeneity among the primary studies. An example illustrates the application of the procedures to actual data and the differences among the results. This research was supported by Grant HS 05936 from the Agency for Health Care Policy and Research to Harvard University.     

The peripheral position of sex in a psychotherapy: An illustrative case of a mirror transference

Understanding the role of sexualization in a depressed patient gives us the opportunity to re-examine the place of sexual activity in psychopathology. The self psychological concept of the mirror transference is used to explain the therapist's activity in the case illustration.     

Lines through the origin—is NO INT the answer?

The fitting of a straight line that must pass through (0, 0) is a frequently encountered application of linear regression. Many computer packages provide a least-squares option sometimes identified as NO INT, or even NOINT, or as ‘suppressing the intercept’. Often these procedures are invalid or do not correspond to the most suitable model. This paper questions the least-squares-line approach and suggests some alternatives. Two measures are proposed for comparing the fit of alternative models.     

Sexual identity in the ghetto

The more things change, the worse they get.Presented April 18, 1991, Duke University, at the Department of Psychiatry's Grand Rounds, this paper condenses, integrates and updates the author's earlier publication. Acknowledgement and thanks for funding and professional sponsorship of the four research studies this paper draws from are selectively due to the Eugene and Agnes E. Meyer Foundation, the Edgar Stern Family Fund, The National Institute for Mental Health, the Baltimore-Washington Institute for Psychoanalysis and the Department of Psychiatry, Children's Hospital National Medical Center.     

Defining child abuse in Hong Kong

Definitions of child abuse are culturally driven. Hong Kong, with a predominantly Chinese population, has managed to eradicate much of the societal abuse that children suffer elsewhere in Asia. Professional and government attention has now shifted to child abuse and neglect within the family. The paper, based on interviews with key professionals. analysis of policy documents and practice records examines traditional Chinese parent-child relationships. the status of parental authority and corporal punishment and changes in contemporary Hong Kong family life. It goes on to outline the development of responses to child abuse in Hong Kong, some of the dilemmas that professionals face in defining abuse and areas for future research.     

Generalized Laplacian approximations in Bayesian inference

This paper presents a new Laplacian approximation to the posterior density of η = g(θ). It has a simpler analytical form than that described by Leonard et al. (1989). The approximation derived by Leonard et al. requires a conditional information matrix R_η to be positive definite for every fixed η. However, in many cases, not all R_η are positive definite. In such cases, the computations of their approximations fail, since the approximation cannot be normalized. However, the new approximation may be modified so that the corresponding conditional information matrix can be made positive definite for every fixed η. In addition, a Bayesian procedure for contingency-table model checking is provided. An example of cross-classification between the educational level of a wife and fertility-planning status of couples is used for explanation. Various Laplacian approximations are computed and compared in this example and in an example of public school expenditures in the context of Bayesian analysis of the multiparameter Fisher-Behrens problem.     

CALGARY FAMILY INTERVENTION MODEL: ONE WAY TO THINK ABOUT CHANGE

This article defines and describes the Calgary Family Intervention Model (CFIM). CFIM is an organizing framework conceptualizing the intersect between a particular domain (i.e., cognitive, affective, or behavioral) of family functioning and a specific intervention offered by a health professional. Examples and discussion of interventions such as storying the illness experience, encouraging respite, and asking interventive questions are presented. CFIM is one way that health professionals can conceptualize about change.