Nuclear hormone receptors, metabolism, and aging: what goes around comes around. Transcription factors link lipid metabolism and aging-related processes

Previous studies have linked the mysterious and inevitable process of aging to essential processes such as metabolism, maturation, and fecundity. Each of these processes is controlled to a large extent by nuclear hormone receptors (NHRs). NHRs also play important roles in the control of periodical processes, the most recently implicated being circadian rhythm. This Review stresses the mounting evidence for tight relationships between each of these NHR-regulated processes and the processes of aging.     

Using cluster analysis in program evaluation

The conventional way to measure program impacts is to compute the average treatment effect; that is, the difference between a treatment group that received some intervention and a control group that did not. Recently, scholars have recognized that looking only at the average treatment effect may obscure impacts that accrue to subgroups. In an effort to inform subgroup analysis research, this article explains the challenge of treatment group heterogeneity. It then proposes using cluster analysis to identify otherwise difficult-to-identify subgroups within evaluation data. The approach maintains the integrity of the experimental evaluation design, thereby producing unbiased estimates of program impacts by subgroup. This method is applied to data from the evaluation of New York State's Child Assistance Program, a reform that intended to increase work and earnings among welfare recipients. The article interprets the substantive findings and then addresses the advantages and disadvantages of the proposed method.     

The Social Participation of Blacks: A Proposed Synthesis of Two Competing Theories

Discrepant findings have typified the research concerning the social participation of blacks in America. The bulk of the findings would seem to posit three competing theories, one emphasizing low participation levels on the part of blacks, and the later two emphasizing high levels of social participation. These theories are examined and a synthesis of the "isolation" and "compensation" models is proposed. By examining both formal and informal types of social participation on the part of blacks, it is argued that both theories are viable toward explaining variation within black participation levels in particular and toward mediating the discrepant findings as they have been previously offered in general. Some support is found for such a proposed synthesis.     

Longitudinal Penalized Functional Regression for Cognitive Outcomes on Neuronal Tract Measurements

We describe and analyze a longitudinal diffusion tensor imaging (DTI) study relating changes in the microstructure of intracranial white matter tracts to cognitive disability in multiple sclerosis patients. In this application the scalar outcome and the functional exposure are measured longitudinally. This data structure is new and raises challenges that cannot be addressed with current methods and software. To analyze the data, we introduce a penalized functional regression model and inferential tools designed specifically for these emerging types of data. Our proposed model extends the Generalized Linear Mixed Model by adding functional predictors; this method is computationally feasible and is applicable when the functional predictors are measured densely, sparsely or with error. An online appendix compares two implementations, one likelihood-based and the other Bayesian, and provides the software used in simulations; the likelihood-based implementation is included as the lpfr() function in the R package refund available on CRAN.     

Estimation and Confidence Intervals for Clock Offset in Networks with Bivariate Exponential Delays

There is a large and increasing literature on statistical modeling-based estimation of the offset between two clocks. Recent work has focused on the construction of confidence intervals for offset. However, in most of this work it has been assumed that the network delays that occur during the synchronization process are independent. The network delays are often modeled as independent exponential random variables. Thus, we introduce the use of a bivariate exponential distribution to capture the anticipated correlation between the network delays and derive a maximum likelihood estimator and a confidence interval procedure for the offset parameter. We then illustrate how use of the independent model for network delays can lead to improper inference about the offset parameter.