Types of Workplace Social Support in the Prediction of Job Satisfaction

Research on social support and job satisfaction has yielded mixed results, partly because studies have rarely examined different types of workplace social support, such as collegial support, task support, coaching, and career mentoring. This study identified the relative contributions of different types of social support to job satisfaction and explored the relationship between social support and job tenure. Overall, social support accounted for approximately 17% of the variance in job satisfaction and 9% of the variance in job tenure. Career mentoring and task support were the types of social support most predictive of job satisfaction. Coaching and task support were the types of social support most predictive of job tenure.     

Employment Exits and the Race Gap in Young Women's Employment*

Objective. A race gap in employment that disadvantages young African‐American women has emerged for the first time in U.S. history. This article addresses the extent to which race differences in employment entry, exits, or both are responsible for the gap. Methods. The article relies on event‐history analysis using NLSY data. Results. Analyses show that differences in rates of exit, not entry, explain the race gap. Factors encouraging higher exit rates among African‐American than white women include lower AFQT scores and greater numbers of children. Conclusion. These findings raise questions about the utility of focusing on employment processes at the point of employment entry, at least for processes involving young women. The importance of exits in understanding race differences in women's employment calls attention to processes within firms that present barriers to African‐American women.     

A Multiple State Model for Disability Using the Decomposition of Death Probabilities and Cross-Sectional Data

ABSTRACT

We split the components corresponding to the disability-free survival probability, and the disability survival probability. Our analysis is conducted for men and women separately, for age groups over 64 years. We discuss the estimation of a multiple state model under several scenarios when only a single survey of cross-sectional data is available. The conclusions are used to discuss the disability level of the Spanish elderly population and are helpful to develop welfare programs and insurance products.     

Asymptotic Results for a Generalized Pólya Urn with “Multi-Updating” and Applications to Clinical Trials

In this article, a new Pólya urn model is introduced and studied; in particular, a strong law of large numbers and two central limit theorems are proved. This urn generalizes a model studied in Berti et al. (2004 Berti , P. , Pratelli , L. , Rigo , P. ( 2004 ). Limit theorems for a class of identically distributed random variables . Ann. Probab. 32 ( 3A ): 2029 – 2052 . [Google Scholar]), May et al. (2005 May , C. , Paganoni , A. M. , Secchi , P. ( 2005 ). On a two-color generalized Pólya urn . Metron 63 ( 1 ): 115 – 134 . [Google Scholar]), and in Crimaldi (2007 Crimaldi , I. ( 2007 ). Almost sure conditional convergence for a generalized Pólya urn. Submitted. Available at: http://amsacta.cib.unibo.it/archive/00002468  [Google Scholar]), and it has natural applications in clinical trials. Indeed, the model includes both delayed and missing (or null) responses. Moreover, a connection with the conditional identity in distribution of Berti et al. (2004 Berti , P. , Pratelli , L. , Rigo , P. ( 2004 ). Limit theorems for a class of identically distributed random variables . Ann. Probab. 32 ( 3A ): 2029 – 2052 . [Google Scholar]) is given.     

Correction of Bias in Imputing Missing Values of Categorical Variables

Markov Chain Monte Carlo (MCMC) is the most common method used in multiple imputation. However, it is not unbiased when it is applied to imputations of categorical variables. The literature has considered the problem for binary variables with only two levels. In this article, we consider more general situations. We not only evaluate the bias associated with the imputation of categorical variables using the MCMC method, but also introduce a method to correct the bias. A simulation study is conducted and an application is provided to demonstrate the advantages of using the correction factors proposed in this article.     

Social work involvement in end of life planning

This cross sectional study examined the factors associated with social workers' involvement in end-of-life (EOL) planning using a random sample of NASW members in health and aging. Of the 390 social workers who worked in EOL planning, the majority were involved in health care proxy discussions and counseling with patients. Respondents tended to see barriers to proxy completion as client-related. However, some system barriers were correlated with overall involvement. Factors that predicted social workers' involvement with the health care proxy included age, attitudes, perceptions of barriers, and perceived physician support. Social workers need to attend to the systems in which they operate as well as to client concerns.     

Large Sample Inference for Markovian Exponential Families with Application to Branching Processes with Immigration

This paper presents limit distributions for the score and likelihood-ratio (L.R.) statistic for testing a composite hypothesis involving the mean of the offspring distribution of the Bienaymé-Galton-Watson branching process with immigration (BPWI) when the process is subcritical, critical or supercritical. The BPWI is shown to be a member of a certain Markovian exponential family.