Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Health technology assessment between our health care system and our health

In this contribution, I wish to explore the potential of health technology assessment and ethics for increasing our capacity to pre-empt the shortcomings and undesired consequences of modern health care while maintaining its benefits. Central is the presumption that in case of some health problems this cannot be done unless we explicitly reconsider some features of the modern health care system, especially those related to its strong reliance on scientific rationality and the strong role played by medical professionals. So as to both maintain the benefits of advanced health care and ensure that it produces less reason for concern, we need to reconsider our approach to rationality—and maybe even the way in which we build our health care system around that rationality. That is, we need to introduce an element of reflexivity. Two types of circumstances are being explored in which such reflexivity may prove worthwhile: controversies on side effects, and persistent problems encountered in optimising health care. Drawing on brief discussions of typical cases, we explore the potential of reflexive HTA and its methodical prerequisites. We conclude that ethicists may contribute to reflexive HTA, if they combine a hermeneutic—and often also participative—methodology with a solid understanding of the relation between the health problem under scrutiny and more general critique of the health care system. Insights from the areas of science and technology studies, as well as from social philosophy may be critical items in their tool kit.     

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.     

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.     

AN EFFICIENCY EXPLANATION FOR WHY FIRMS SECOND SOURCE

Firms facing research costs and demand uncertainty may engage in second-sourcing, in which potential suppliers agree to pool production facilities. I show how sellers and buyers both can benefit from the practice. Second-sourcing allows firms to meet a wider range of possible rates of demand and often to supply a given rate of demand at a lower total cost than under non-cooperation. Buyers benefit through a reduced probability of stock-outs and frequently a lower purchase price. Semiconductor industry data are found to be consistent with the paper's predictions.     

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.