Testing for bioequivalence of highly variable drugs from TR‐RT crossover designs with heterogeneous residual variances

Traditional bioavailability studies assess average bioequivalence (ABE) between the test (T) and reference (R) products under the crossover design with TR and RT sequences. With highly variable (HV) drugs whose intrasubject coefficient of variation in pharmacokinetic measures is 30% or greater, assertion of ABE becomes difficult due to the large sample sizes needed to achieve adequate power. In 2011, the FDA adopted a more relaxed, yet complex, ABE criterion and supplied a procedure to assess this criterion exclusively under TRR‐RTR‐RRT and TRTR‐RTRT designs. However, designs with more than 2 periods are not always feasible. This present work investigates how to evaluate HV drugs under TR‐RT designs. A mixed model with heterogeneous residual variances is used to fit data from TR‐RT designs. Under the assumption of zero subject‐by‐formulation interaction, this basic model is comparable to the FDA‐recommended model for TRR‐RTR‐RRT and TRTR‐RTRT designs, suggesting the conceptual plausibility of our approach. To overcome the distributional dependency among summary statistics of model parameters, we develop statistical tests via the generalized pivotal quantity (GPQ). A real‐world data example is given to illustrate the utility of the resulting procedures. Our simulation study identifies a GPQ‐based testing procedure that evaluates HV drugs under practical TR‐RT designs with desirable type I error rate and reasonable power. In comparison to the FDA's approach, this GPQ‐based procedure gives similar performance when the product's intersubject standard deviation is low (≤0.4) and is most useful when practical considerations restrict the crossover design to 2 periods.     

Staff Development as a School Climate Intervention to Support Transgender and Gender Nonconforming Students: An Integrated Research Partnership Model for School Counselors and Counselor Educators

ABSTRACT

This article posits that an integrative research partnership model can assist school counselors in addressing the marginalization of transgender students in schools through staff development. A methodological integration of action research and program evaluation through quantitative and qualitative data collection is explained, and a collaborative process is highlighted. A case example is provided to demonstrate the use of the design.     

Changing Trends of Mothers’ Active and Passive Childcare Times

This paper explores how mothers’ allocation of types of time with children and the determinants of this allocation have changed during 1981–1997 in the United States, using Time Use Longitudinal Panel Study and Family Interaction, Social Capital and Trends in Time Use. Data reveal that active time with children has increased for the case of educated working mothers with young children. Estimations also provide evidence that although different uses of time are substitutes; active time is less sensitive than passive. Moreover, the relationship between active and passive time with children has changed over time.     

Climate change and population migration in Brazil’s Northeast: scenarios for 2025–2050

This research contributes to an understanding of the relationship between climate change, economic impacts and migration. We model the long-term relationship (up to 45 years of projection) between demographic dynamics—particularly migration—driven by changes in the performance of the economy due to climate changes in the Northeast region of Brazil. The region is of particular relevance to the study of climate change impacts given its large human population (28% of Brazil’s population) and high levels of impoverishment, having an extensive semi-dry area which will be severely impacted by growing temperatures. Ultimately, the integrated model generates state- and municipal-level migration scenarios based on climate change impacts on the primary economic sectors and their articulations with other sectors. Results suggest that the predicted climate changes will impact severely the agriculture sector in the region, acting as a potential migration push factor to other regions in the country. Finally, we discuss how the increased vulnerability of some groups, particularly migrants, can be factored into Brazilian public policy and planning.     

An Analysis of Student Satisfaction: Full-Time vs. Part-Time Students

This paper examines how full-time or part-time status affects students’ level of satisfaction with their degree programs. For our analysis, we obtained data from a survey of graduate students. The survey was conducted at a public university in Spain from 2001 to 2004. The decision to undertake paid employment while studying emerges as one of the key determinants of student satisfaction. In particular, our findings indicate that students who hold a part-time job while studying are more likely to express less satisfaction with their college experience.     

Household Saving Behavior and the Influence of Family-Owned Business

This study focused on the lifecycle income objective of business-owning (farm and nonfarm) households. We hypothesized that the complex relationship between household and business management decisions had the potential to challenge predictions from standard household savings theory. Specifically, we tested for differences in saving behavior of these entrepreneurial households relative to the average US household. A limited dependent variable model was performed, keying in on the saving behavior and ability of household respondents in the Survey of Consumer Finances for 2007. The estimation results indicated that, along with standard demographic influences of savings models, households owning a farm or nonfarm business had a significantly higher likelihood of maintaining private saving in a given year. Our results highlight the necessity for future research on household saving behavior to account for the differing objectives and choice sets faced by households that own businesses when conducting analyses of household saving.     

The influence of FDA advisory information and black box warnings on individual use of prescription antidepressants

We examine how use of antidepressant medications is influenced by Food and Drug Administration (FDA) warnings about the increased risk of suicidality associated with pediatric antidepressant use. With individual-level data on antidepressant use from the Medical Expenditure Panel Survey, we consider whether consumer responses to FDA warnings differ among targeted (children) and non-targeted (adult) age-groups. Because the warning labels specifically mentioned new users, we examine separately the effects of the warnings on initiations of antidepressant therapy and on continued use of antidepressants. We find evidence consistent with reduced initiation of antidepressant use among the intended population of children, and that usage among children with more highly educated parents responded earlier to FDA information. However, we also find spillover effects of reduced initiation among the non-targeted population of adults. Overall, our results indicate that the FDA warning may have led consumers to perceive risks beyond those specifically mentioned.     

AD HOC MODEL BUILDING USING TIME-VARYING PARAMETER MODELS*

Decision support for managers and policy makers, such as required in planning and evaluation efforts, often requires ad hoc behavioral modeling to account for context-specific phenomena and to handle data limitations. This paper introduces a systematic approach useful for meeting these requirements in which time-varying parameter estimation plays an important role. A case study evaluating the impacts of public policy actions on residential natural gas conservation illustrates the approach.