Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Multi-valued strategy-proof social choice rules

In this paper we introduce a new definition of strategy-proofness for multi-valued social choice correspondences. We prove two Gibbard-Satterthwaite type results for strategy-proof social choice correspondences. These results show that allowing multiple outcomes as social choices will not necessarily lead to an escape from the Gibbard-Satterthwaite impossibility theorem. Received: 24 January 2001/Accepted: 19 March 2001     

Institutional Constraints and Deforestation: An Application to Mexico

Following North (1990), this article hypothesizes that effective rural institutions may impose additional costs on tropical deforestation through agricultural conversion. This allows a formal agricultural household analysis of institutional constraints on deforestation and therefore a method of empirically testing whether there is any significant difference in the actual level of forest land conversion under institutional constraints compared to the level of conversion under pure open access. A dynamic panel analysis for agricultural planted area in Mexico at state level and over the 1960–85 period confirms that institutional constraints on land clearing affected deforestation during the pre-NAFTA era.     

Characterizations of two power indices for voting games with r alternatives

In the first three sections of this paper we present a set of axioms which provide a characterization of an extension of the Banzhaf index to voting games with r alternatives, such as the United Nations Security Council where a nation can vote “yes”, “no”, or “abstain”. The fourth section presents a set of axioms which characterizes a power index based on winning sets instead of pivot sets. Received: 4 April 2000/Accepted: 30 April 2001     

Telecommuting: The future of work, corporate culture, and American society

Conclusion Throughout American history, first on the family farm and now in modern day business institutions, the workplace has been a stabilizing institution in American society that has anchored the ongoing, informal interactions occurring outside the workplace. In 1900, few Americans had a private mode of transportation. Barely 4,000 passenger automobiles were sold in 1900, and while horses were common, they were used primarily for farming, public transportation, and commercial activity in cities. By 1930, nearly 40 million cars had been added to America’s streets. The automobile recast life and work in central cities and eventually the suburbs.     

Efe fathers: one among many? A comparison of forager children's involvement with fathers and other males

The study reported describes Efe (pygmy) forager one-, two-, and three-year-olds' involvement with males. The Efe of northeastern Zaïre were chosen because their social organization allows us to examine hypotheses based on studies in Western, technologically complex societies about the distinctive role fathers play in the lives of their young children. Behavioral observations of Efe children's day-to-day activities with fathers, men and boys were recorded using a focal subject sampling technique (Altmann, 1974). Two behavioral measures were created to capture the extent to which males were involved with children: Social engagement describes males' involvement with children and social attention describes eavesdropping by children on males' everyday activities. Eight one-year-olds, 7 two-year-olds and 8 three-year-olds were each observed for six, one-hour observation sessions that were distributed evenly over the daylight hours. Data were analyzed using the traditional measure of involvement (e.g., adult males) and using a newly developed measure of the involvement of the average individual (e.g., average adult mate). Comparisons at each of the ages showed that fathers were consistently like other men in the extent to which children participated in social activities with them and watched their activities. Only fathers' level of social engagement declined significantly as children grew older. Boys' role relative to other males became increasingly distinctive as children aged. The findings suggest that Efe fathers may not be unique in the same sense assumed by Western study ideals, and raise questions about the special status given to fathers in Western theory and data. The patterning of mate involvement with children is discussed in terms of Efe community life, and in terms of Efe children's developing understanding of their relationship with fathers and other males.     

Generating random variates from D-distributions via substitution sampling

Laud et al. (1993) describe a method for random variate generation from D-distributions. In this paper an alternative method using substitution sampling is given. An algorithm for the random variate generation from SD-distributions is also given.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.