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.     

Standing on Their Own Two Feet: How the New Public Charge Rules Could Impact Non-European LPR Applicants

Population Research and Policy Review - In February 2020, the U.S. government began to implement a new Public Charge rule that greatly expands the definition of “public charge” when...     

Changing Frameworks in Attitudes Toward Abortion

For more than two decades, legal abortion has been the subject of heated political debate and adversarial social movement activity; however, national polls have shown little change in aggregate levels of support for abortion. This analysis examines how the determinants of abortion attitudes have changed between 1977 and 1996, using data from the General Social Surveys. While in early time periods, whites were more approving of abortion than blacks, that pattern had reversed by the late 1980s. After controlling for other factors, older people are more accepting of abortion throughout the two decades, while gender is generally unrelated to abortion views. Catholic religion weakens slightly as a predictor of abortion attitudes, while religious fundamentalism and political liberalism increase in explanatory power. The associations between attitudinal correlates and abortion approval also change over this time period. Religiosity becomes a less powerful predictor of abortion attitudes, while respondents' attitude toward sexual freedom and belief in the sanctity of human life increase in their predictive power. Support for gender inequality remains a weak but stable predictor of abortion attitudes. This pattern of results suggests that the public is influenced more by the pro-life framework of viewing abortion than by the pro-choice perspective.     

Becoming Custodial Dads: Exploring Parenting Among Low‐Income and Working‐Class African American Fathers

The authors use an ecological framework and grounded theoretical analysis to explore the circumstances in which working‐class and low‐income custodial African American fathers gain custody of their children, their transition from part‐time to full‐time parents, and the role of support networks in enhancing or inhibiting these men's parenting. Twenty‐four men from an impoverished Midwestern urban area participated in the study. The findings suggest that these men, and perhaps others sharing their demographic profiles, generally become parents by default and are often reluctant to take on a full‐time, single parenting role. Adaptation to the role seems to be enhanced by these men's use of extended kin support networks and shared living arrangements. However, low wages, a lack of sufficient assistance from public assistance programs, and informal custody arrangements often inhibit their fathering.     

Measuring agreement between two statistics with applications to age standardization

Summary.  We detail a general method for measuring agreement between two statistics. An application is two ratios of directly standardized rates which differ only by the choice of the standard. If the statistics have a high value for the coefficient of agreement then the expected squared difference between the statistics is small relative to the variance of the average of the two statistics, and inferences vary little by changing statistics. The estimation of a coefficient of agreement between two statistics is not straightforward because there is only one pair of observed values, each statistic calculated from the data. We introduce estimators of the coefficient of agreement for two statistics and discuss their use, especially as applied to functions of standardized rates.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.     

Consumption and Saving Behavior of Older and Younger Baby Boomers in Korea

The 1998 Korean Survey of Family Income and Expenditures was used to examine the overall consumption and saving behavior of Korean baby boomers and compared the differences in consumption and saving behavior between older and younger boomers. The t -test results indicated that the younger boomers allocated a significantly higher percentage of their expenditures on food away from home, household appliances, transportation and communication than did the older boomers, whereas the older boomers spent higher amounts and allocated larger budget shares on their children's education than did the younger boomers. The results of Ordinary Least-Squares (OLS) regression analysis showed that, holding other factors constant, older boomers not only spent significantly more in the total consumption expenditures and education expenditures, but older boomers also saved significantly less than did younger boomers.     

Assessment of influence in non-linear measurement error models

We consider the assessment of outliers and influential observation in non-linear measurement error models. Residuals, leverage measures and case-deletiondiagonostics are examined. The method of local influence is also applied to the models. In particular, the perturbation of measurement error variances has been found useful in assessing the adequancy of the model assumptions. A numerical example is given to illustrate the application of the diagonostics.     

Bankrupt Rhetoric: How Misleading Information Affects Knowledge about Social Security

Most citizens know little about politics. Scholars often attributepolitical ignorance to individual-level factors, but we concentrateon the quality of the information environment. Employing a combinationof experimental methods and content analysis, we code statementsfrom the 1998–99 debate over Social Security reform aseither misleading or not misleading. Then, using surveys conductedduring the debate, we examine the impact of individual- andenvironmental-level variables on political knowledge about theprogram’s future. We show that misleading statements aboutSocial Security’s future cause some citizens to get animportant fact about the program wrong. More precisely, manycitizens mistakenly believe that Social Security will run outof money because political elites occasionally use words thatlead to overly pessimistic assessments of the program’sfinancial future. Our findings have important implications forpolicymakers who are attempting to remake America’s largestfederal program, scholars who study citizen competence, andcitizens in a representative democracy.