Do flexible work schedules reduce turnover in U.S. federal agencies?

Agency theory suggests that when agencies adopt flexible work schedules, employees will be more likely to remain with the organization, because these programs demonstrate that the organization cares about their well-being in that flexible work schedules give them more flexibility regarding when, where, and how they perform their work. To test this proposition, cross-sectional panel data at the agency level were obtained from two federal government sources: Federal Employee Viewpoint Survey and FedScope. Furthermore, transfers and quits were the two forms of turnover examined. After lagging the independent variables behind turnover over several years so as to provide a robust test of causality, the results show only limited support for agency theory. Specifically, teleworking was found to lower quits. However, teleworking was not found to reduce transfers or turnover, in general. Furthermore, alternative work schedules were not found to have an impact on quits, transfers, or turnover generally.     

A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

Statistical Methods & Applications - In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The...     

Empirical Likelihood Inference for the Rao‐Hartley‐Cochran Sampling Design

The Hartley‐Rao‐Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley‐Rao‐Cochran sampling design. The approach proposed intrinsically incorporates sampling weights, auxiliary information and allows for large sampling fractions. It can be used to construct confidence intervals. In a simulation study, we show that the coverage may be better for the empirical likelihood confidence interval than for standard confidence intervals based on variance estimates. The approach proposed is simple to implement and less computer intensive than bootstrap. The confidence interval proposed does not rely on re‐sampling, linearization, variance estimation, design‐effects or joint inclusion probabilities.     

Making Professional Decisions in Research: Measurement and Key Predictors

The professional decision-making in research (PDR) measure was administered to 400 National Institutes of Health (NIH)-funded and industry-funded investigators, along with measures of cynicism, moral disengagement, compliance disengagement, impulsivity, work stressors, knowledge of responsible conduct of research (RCR), and socially desirable response tendencies. Negative associations were found for the PDR and measures of cynicism, moral disengagement, and compliance disengagement, while positive associations were found for the PDR and RCR knowledge and positive urgency, an impulsivity subscale. PDR scores were not related to socially desirable responding, or to measures of work stressors and the remaining impulsivity subscales. In a multivariate logistic regression analysis, lower moral disengagement scores, higher RCR knowledge, and identifying the United States as one’s nation of origin emerged as key predictors of stronger performance on the PDR. The implications of these findings for understanding the measurement of decision-making in research and future directions for research and RCR education are discussed.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Development and validation of a Citizenship Attributional Style Questionnaire

Attribution theory remains popular in the social sciences and often informs education studies. However, attributional style questionnaires tend to reflect the context-dependent character of the theory and existing measures have been found to have poor psychometric properties. Clearly, both issues need to be carefully considered by researchers prior to them applying any scales that incorporate attributional dimensions. Here we report on the development of a reliable and valid measure that applies an attributional style within the context of citizenship. Two separate studies were conducted to inform the development of the Citizenship Attributional Style Questionnaire (CASQ). The factor loadings of eight positive and eight negative events for the internality and stability dimensions were found to range between .41 and .75. The Cronbach’s alpha reliability of positive and negative events were found to be .79 and .74, respectively. While CASQ is seen to be a reliable and valid measure, the results also indicate broader psychometric properties than many of the instruments currently used in studies with an attributional approach.     

Effects of Network Approval on Accounts of Commitment Trajectories in Intraracial and Interracial Relationships

The current study used dyadic data to investigate the impact of relationship type and social support on the retrospective accounts of commitment trajectories of romantic relationships. Past research suggests that social support is a positive contributor to relationship stability and commitment, which may be especially true for partners in interracial relationships who face broader societal opposition than intraracial couples. Using multilevel modeling, we investigated the effects of sex, relationship type, and social support on reports of commitment. Results showed differences in trajectories of commitment based on couple type (interracial vs. intraracial) for both men and women. Social support was found to have an especially strong impact for women in interracial relationships compared with women in intraracial relationships, but there was no differential impact among men.     

On the Nearness of Records to Population Quantiles with Respect to Order Statistics in the Sense of Pitman Closeness

In this paper, Pitman closeness criterion is used to compare the nearness of record values and order statistics from two independent samples to a specific population quantile of the parent distribution while the underlying distributions are the same. General expressions for the associated Pitman closeness probability are obtained when the support of the parent distribution is bounded and also unbounded. Some distribution-free results are achieved for symmetric distributions. The exponential and uniform distributions are considered for illustrative proposes and exact expressions are obtained in each case.     

Estimating the population proportion in modified ranked set sampling methods

In this paper, proportion estimators and associated variance estimators are proposed for a binary variable with a concomitant variable based on modified ranked set sampling methods, which are extreme ranked set sampling (ERSS), median ranked set sampling (MRSS), percentile ranked set sampling (Per-RSS) and L ranked set sampling (LRSS) methods. The Monte Carlo simulation study is performed to compare the performance of the estimators based on bias, mean squared error, and relative efficiency for different levels of correlation coefficient, set and cycle sizes under normal and log-normal distributions. Moreover, the study is supported with real data application.