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.     

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.     

Fast retraction of evidence in a probabilistic expert system

We present and justify a propagation algorithm to facilitate the simultaneous calculation, for every node in a probabilistic exper system of the distribution of the associated random quantity, conditional on all the evidence obtained about the remaining nodes.     

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.     

Estimation of parameters for rounded data from non-normal distributions

This paper is concerned with how standard estimation procedures perform in terms of eficiency for non-normal rounded data. Previous research has shown that the loss in eficiency due to rounding normal data is small. However, evidence from the non-normal distribution considered in this paper suggests, if rounding is coarse or the distribution is very skewed the loss in efficiency due to rounding can be considerable.     

Differences in preferred level of arousal in two sub-groups of problem gamblers: A preliminary report

Twelve problem poker machine players and thirteen horse race gamblers (20 males and 5 females; age range 28–69) completed a series of questionnaires which assessed levels of anxiety, their preferred state of arousal and their motivations to gamble. As predicted, problem poker machine gamblers were found to be more anxious and reported avoiding arousal more frequently than the horse race gamblers. Alternately, problem horse race gamblers were found to prefer heightened levels of arousal and appeared to gamble to achieve these optimal levels of arousal. However, there was no difference between the groups on proneness to boredom. The present results provide evidence which is consistent with the Reversal theory and its application to the field of problem gambling.