A course for clinical trial personnel in clinical study designs, randomization, allocation schedules, and interactive response systems

This continuing education course for professionals involved in all areas of clinical trials integrates concepts related to the role of randomization in the scientific process. The course includes two interactive lecture and discussion sections and a workshop practicum. The first interactive lecture introduces basic clinical trial issues and statistical principles such as bias, blinding, randomization, control groups, and the importance of formulating clear and discriminating clinical and statistical hypotheses. It then focuses on the most commonly used clinical study designs and the corresponding patient randomization schemes. The second interactive lecture focuses on the implementation of randomization of patients and drug supply through allocation and component ID schedules. The workshop practicum, conducted in small groups, enables students to apply the lecture concepts to real clinical studies. Flexibility was built into the workshop practicum materials to allow the course content to be customized to specific audiences, and the interactive lecture sessions can be stretched to cover more advanced topics according to class interest and time availability.     

Vulnerable young people and substance misuse: expanding on the risk and protection‐focused approach using social psychology

This paper critically reviews recent research exploring risk and protective factors for the development of problematic substance use in populations of young people. Specific populations of young people who are most vulnerable to developing problematic patterns of use are identified, and alterations to methods of data collection which would improve the ability of local authorities to monitor these populations and more efficiently target them for early preventative interventions are highlighted. It is argued that social‐psychological research techniques and approaches should be used to complement a risk and protection‐focused approach in order to improve the design and evaluation of interventions, and provide decision‐aids for practitioners when assessing the needs of vulnerable young people. Examples are provided to demonstrate the utility of social psychology in this regard, and the paper concludes with specific recommendations for future research and services. Copyright © 2009 John Wiley & Sons, Ltd.     

LEGISLATING LOVE: The Effect of Child Support and Welfare Policies on Father–child Contact

Reducing non-marital childbearing and making nonresidential fathers take greater responsibility for their children were identified as goals of numerous policy changes since the 1980s. Child-support award rates for children born to unmarried parents have been quite low historically, leading lawmakers to focus on increasing both award and payment rates for this group. Nonmarital fathers are also much less likely to have contact with their children. Although evidence suggests that policy efforts increase child support awards and receipt, the link between child support policies, child support outcomes, and father-child contact has received less attention. This paper uses data from the Survey of Income and Program Participation on children born between 1985–1997 to investigate the relationship between child-support award and receipt and the amount of contact that fathers have with their non-residential children. Since it is likely that both of these behaviors are, in part, determined by unobservable characteristics of the father, we estimate an instrumental variables Tobit model. The model is identified by our assumption that child support policy variables can impact child support awards and payments, but father-child contact cannot be directly legislated. Our results suggest that there are unintended, but desirable effects of child support establishment and collection. Policies to collect child support not only increase financial resources to families, but through their impact on payments increase visitation and contact between these children and their fathers. The estimated impact of receiving child support on contact is more than 27 days per year.An earlier version of this paper was presented at the Annual Meetings of the American Economic Association, Washington DC, January 2003 and the Annual Meetings of the Association of Public Policy and Management, November 2003. Support from NICHD Grant # HD30944 is gratefully acknowledged. We would like to thank Suzann Eshleman for excellent computer programming and James Scully for providing us with data on genetic testing laws.     

Characteristics of female perpetrators and victims of dating violence

Although many researchers have explored the topic of dating violence, limited attention has been paid to female perpetrators. Very little research has examined variables that facilitate aggression for females in dating relationships. In an effort to investigate distinct types of violent behavior, the present study separated females who experience dating violence into three categories (bi-directional aggression, perpetrator-only, and victim-only) and compared them with a control group not previously exposed to interpersonal violence. The purpose of this study was to examine variables that discriminate violent females from non-violent females. Variables that were hypothesized to be associated with aggressive behavior and investigated in the current study were interparental aggression, self-esteem, love attitudes, and alcohol use. Three hundred female college students responded to multiple self-report questionnaires examining psychological correlates of dating violence. Females in the bi-directional aggression group were more likely to have witnessed their father abuse their mother and scored significantly lower on a measure of self-esteem than non-violent controls. Females in the control group demonstrated higher scores on a measure of mature and selfless love style than did the victim or perpetrator-only participants. There were no significant group differences regarding general alcohol consumption. Implications for prevention and intervention are presented and discussed.     

Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation

Children represent a large underserved population of “therapeutic orphans,” as an estimated 80% of children are treated off‐label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or “borrowing”) of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure‐response information for antiepileptic drugs to pediatrics.     

Compatibility,Leisure, and Satisfaction in Marital Relationships

This study challenges the prevailing view that marital companionship promotes marital satisfaction. By following a cohort of married couples for over a decade and by incorporating several methodological improvements—such as refining the measurement of marital satisfaction, determining how much spouses enjoy doing the leisure activities they pursue together and apart, and using diary data to portray marital leisure patterns—we found that the association between companionship and satisfaction is less robust than previously believed, and that it depends on how often spouses pursue activities that reflect their own and their partner's leisure preferences. Over time, involvement in leisure liked by husbands but disliked by wives, whether as a couple or by husbands alone, is both a cause and a consequence of wives' dissatisfaction.     

Modified quasi-profile likelihoods from estimating functions

We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interest, in order to alleviate some of the problems inherent to the presence of nuisance parameters, such as bias and inconsistency. Indeed, quasi-profile score functions for the parameter of interest have bias of order O(1)$\mathrm{O}(1)$, and such bias can lead to poor inference on the parameter of interest. The higher-order adjustments are obtained so that the adjusted quasi-profile score estimating function is unbiased and its variance is the negative expected derivative matrix of the adjusted profile estimating equation. The modified quasi-profile likelihood is then obtained as the integral of the adjusted profile estimating function. We discuss two methods for the computation of the modified quasi-profile likelihoods: a bootstrap simulation method and a first-order asymptotic expression, which can be simplified under an orthogonality assumption. Examples in the context of generalized linear models and of robust inference are provided, showing that the use of a modified quasi-profile likelihood ratio statistic may lead to coverage probabilities more accurate than those pertaining to first-order Wald-type confidence intervals.     

Analysis of growth curve data by using cubic smoothing splines

Longitudinal data frequently arises in various fields of applied sciences where individuals are measured according to some ordered variable, e.g. time. A common approach used to model such data is based on the mixed models for repeated measures. This model provides an eminently flexible approach to modeling of a wide range of mean and covariance structures. However, such models are forced into a rigidly defined class of mathematical formulas which may not be well supported by the data within the whole sequence of observations. A possible non-parametric alternative is a cubic smoothing spline, which is highly flexible and has useful smoothing properties. It can be shown that under normality assumption, the solution of the penalized log-likelihood equation is the cubic smoothing spline, and this solution can be further expressed as a solution of the linear mixed model. It is shown here how cubic smoothing splines can be easily used in the analysis of complete and balanced data. Analysis can be greatly simplified by using the unweighted estimator studied in the paper. It is shown that if the covariance structure of random errors belong to certain class of matrices, the unweighted estimator is the solution to the penalized log-likelihood function. This result is new in smoothing spline context and it is not only confined to growth curve settings. The connection to mixed models is used in developing a rough testing of group profiles. Numerical examples are presented to illustrate the techniques proposed.