Predicting Condom Use Outcomes via the Information Motivation Behavioral Skills Model: An Analysis of Young Black Men

Objectives: This study examines the relationships between information motivation behavioral skills model constructs and their associations with consistent condom use and condom use problems among young Black men. Methods: The authors use baseline data collected from 702 participants in a randomized controlled trial. Analyses involved path modeling and bootstrapped standard errors to estimate associations. Results: Motivation had the largest association with consistent condom use, whereas condom application skills had the largest association with condom use problems. Conclusion: Motivation is the most important predictor of consistent condom use, whereas condom application skills are the most important predictor of condom use problems.     

Roles of organizers and champions in building campus-community prevention partnerships

OBJECTIVE: A campus-community partnership can be an effective vehicle for launching environmental strategies to prevent college alcohol-related problems. In this study, the authors' primary aim was identifying key factors that facilitate or impede colleges' efforts to build campus-community partnerships. PARTICIPANTS AND METHODS: From fall 2004 to summer 2006, administrators at five 4-year colleges participated in a multisite case study. Level of partnership development was the primary outcome. RESULTS: Three interrelated factors facilitated higher-developed partnerships: college staff assigned to facilitate the partnerships who worked as community organizers, higher-level college administrators who served as aggressive champions, and community initiation of the partnership. The authors did not observe this trio of factors among the less-developed partnerships. A lack of administrative support made it more difficult for a champion to emerge, a college administrator who staunchly advocated for a campus-community partnership, and for those assigned to facilitate the partnership to carry out their work. CONCLUSIONS: Colleges should appoint higher-level administrators to serve as champions, while also ensuring that those assigned to facilitate a partnership can apply community organizing skills.     

On two-dimensional optimal controlled nearest proportional to size sampling designs

Using quadratic programming and utilizing the concept of ‘nearest proportional to size sampling design’, we propose a method for two-dimensional optimal controlled selection, which ensures zero probability to non-preferred samples. An alternative strategy for estimation of population total and variance is also suggested. The utility of the proposed procedure is demonstrated with the help of examples.     

Internal Migration and Rural Inequalities in India

Population Research and Policy Review - The study examines the effects of seasonal and permanent migration on rural inequalities in India. We apply the counterfactual method to estimate income...     

Some remarks on classical and bayesian reliability estimation of binomial and poisson distributions

The problems of estimating the reliability function and Pr{X₁+...+X_k ≤ Y} are considered. The random variables X’s and Y are assumed to follow binomial and Poisson distributions. Classical estimators available in the literature are discussed and Bayes estimators are derived. In order to obtain the estimators of these parametric functions, the basic role is played by the estimators of factorial moments of the two distributions.     

A Simple Distribution-Free Algorithm for Generating Simulated High-Dimensional Correlated Data with an Autoregressive Structure

A distribution-free method to generate high-dimensional sequences of dependent variables with an autoregressive structure is presented. The quantile or fractile correlation (i.e., the moment correlation of the quantiles) is used as measure of dependence among a set of contiguous variables. The proposed algorithm breaks the sequence in small parts and avoids having to define one large correlation matrix for the entire high-dimensional sequence of variables. Simulations based on proteomics data are presented. Results suggest that negligible or no loss of fractile correlation occurs by splitting the generation of a sequence into small parts.     

Short- and long-run rolling causality techniques and optimal window-wise lag selection: an application to the export-led growth hypothesis

The literature devoted to the export-led growth (ELG) hypothesis, which is of utmost importance for policymaking in emerging countries, provides mixed evidence for the validity of the hypothesis. Recent contributions focus on the time-dependence of the relationship between export and output growth using rolling causality techniques based on vector autoregressive models. These models focus on a short-term view which captures single policy-induced developments. However, long-term structural changes cannot be covered by examinations related to the short-term. This paper hence examines the time-varying validity of the ELG hypothesis for India for the period 1960–2011 using rolling causality techniques for both the short-run and long-run horizon. For the first time, window-wise optimal lag-selection procedures are applied in connection with these techniques. We find that exports long-run caused output growth from 1997 until 2009 which can be seen as a consequence of political reforms of the 1990s that boosted economic growth by generating foreign direct investment opportunities and higher exports. For the short-run, export significantly caused output in the period 1998–2003 which followed a concentration of liberalization measures in 1997. Causality in the reversed direction, from output to exports, only seems to be relevant in the short-run.     

Analysis of ordered categorical data with score averaging: with applications to case-control genetic associations

The trend test is often used for the analysis of 2×K ordered categorical data, in which K pre-specified increasing scores are used. There have been discussions on how to assign these scores and the impact of the outcomes on different scores. The scores are often assigned based on the data-generating model. When this model is unknown, using the trend test is not robust. We discuss the weighted average of a trend test over all scientifically plausible choices of scores or models. This approach is more computationally efficient than a commonly used robust test MAX when K is large. Our discussion is for any ordered 2×K table, but simulation and applications to real data are focused on case-control genetic association studies. Although there is no single test optimal for all choices of scores, our numerical results show that some score averaging tests can achieve the performance of MAX.