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.     

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.     

Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

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.     

A ‘nondecimated’ lifting transform

Classical nondecimated wavelet transforms are attractive for many applications. When the data comes from complex or irregular designs, the use of second generation wavelets in nonparametric regression has proved superior to that of classical wavelets. However, the construction of a nondecimated second generation wavelet transform is not obvious. In this paper we propose a new ‘nondecimated’ lifting transform, based on the lifting algorithm which removes one coefficient at a time, and explore its behavior. Our approach also allows for embedding adaptivity in the transform, i.e. wavelet functions can be constructed such that their smoothness adjusts to the local properties of the signal. We address the problem of nonparametric regression and propose an (averaged) estimator obtained by using our nondecimated lifting technique teamed with empirical Bayes shrinkage. Simulations show that our proposed method has higher performance than competing techniques able to work on irregular data. Our construction also opens avenues for generating a ‘best’ representation, which we shall explore.     

Nonparametric control charts based on runs and Wilcoxon-type rank-sum statistics

In this article, we introduce three new distribution-free Shewhart-type control charts that exploit run and Wilcoxon-type rank-sum statistics to detect possible shifts of a monitored process. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of these charts is that, due to their nonparametric nature, the false alarm rate (FAR) and in-control run length distribution is the same for all continuous process distributions. Tables are provided for the implementation of the charts for some typical FAR values. Furthermore, a numerical study carried out reveals that the new charts are quite flexible and efficient in detecting shifts to Lehmann-type out-of-control situations.     

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.