Bridging between academia and the workplace: lessons learned about translational research on work-family balance

ABSTRACT

Balancing work and family is a continuous and growing challenge, requiring carefully chosen coping strategies. In spite of the growing amount of research on work-family balance, successful, long term solutions are still not readily available to most workers who are trying to cope with the tensions involved in fulfilling both work and family roles. One possible explanation for this lack of translation of research findings in applied settings may lie in how we do work-family research. The present research note presents translational research as a solution to bridge academia and the workplace. More specifically, it shares our experience of a participatory approach to translational research that was adopted in an interdisciplinary research project on work-family balancing strategies. The main objective of this research note is to provide an example of how translational research was carried out in this kind of community-initiated study, and how this approach can facilitate short-term, concrete applications of the knowledge gained from and with the research partners.     

Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis

Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse, from a non asymptotic point of view, the Sampling Importance Resampling (SIR) PF with optimal conditional importance distribution (CID) and the fully adapted APF (FA). We compute the (finite samples) conditional second order moments of Monte Carlo (MC) estimators of a moment of interest of the filtering pdf, and analyse under which circumstances the FA-based estimator outperforms (or not) the optimal Sequential Importance Sampling (SIS)-based one. Our analysis is local, in the sense that we compare the estimators produced by one time step of the different SMC algorithms, starting from a common set of weighted points. This analysis enables us to propose a hybrid SIS/FA algorithm which automatically switches at each time step from one loop to the other. We finally validate our results via computer simulations.     

Psychological Distress in Older Portuguese Gay and Bisexual Men: The Mediating Role of LGBT Community Connectedness

Abstract

Objectives: Examining Psychological Distress (PD) among older Portuguese gay and bisexual men (GBM), and the mediator role of LGBT community connectedness (LGBTCC) of minority stress variables on PD. Methods: We performed a mediation analysis with LGBTCC as mediator between minority stress variables and PD with a sample of 110 elderly GBM. Results: We found moderate PD levels; LGBTCC was a significant mediator between concealment of sexual orientation and PD, but not between internalized stigma and expectations of rejection and PD. Conclusions: More attention is needed to Older Portuguese GBM’s mental health. LGBTCC is an important ameliorating factor for older GBM.     

Unknown Knowns and Known Unknowns: Framing the Role of Organizational Learning in Corporate Social Responsibility Development

Corporate social responsibility (CSR) is now widely seen as an increasingly significant concern for firms because of moral, relational and instrumental motives. Nevertheless, practical aspects and challenges associated with CSR development in firms remains only partially understood. In this setting, the organizational learning (OL) discipline is recurrently put forward as key in the pursuit and successful development of CSR, but the existing literature remains disjointed. This study critically reviews the existing literature to conceptualize how research to date has approached CSR development in terms of OL, and to provide a two‐dimensional structuring framework of the role of OL in CSR development that emphasizes key OL‐related aspects supporting CSR development and goes beyond an organization‐centric viewpoint to consider not only learning within the organization, but also from others, and with others. In particular, the authors identify key learning processes and sub‐processes and critical areas that remain understudied. Overall, the authors propose a macro view of the work done to date at the intersection of OL and CSR, and in doing so help make the ‘OL for CSR development’ scholarship more recognizable as a sub‐discipline.     

Inference in a generalized endpoint-inflated binomial regression model

Generalized endpoint-inflated binomial regression was recently proposed to model count data with large frequencies of both zeros and right-endpoints. Maximum likelihood estimation (MLE) was developed for this model and simulations suggest that the resulting estimates behave well. However, large-sample properties of the MLE have not yet been rigorously established. Such results are however essential for ensuring reliable statistical inference and decision-making. This paper addresses this issue. Identifiability of the generalized endpoint-inflated binomial regression model is first proved. Then, consistency and asymptotic normality of the MLE are established. A simulation study is conducted to assess finite-sample behaviour of the estimator.     

Turkish health professional's attitude toward euthanasia

The cross-sectional study was administrated between April and September 2006. Participants are doctors, nurses, and midwives. Between these dates we met only 750 health staff (doctor, nurse, and midwife). Six hundred thirty-two of them responded to our questionnaire, 122 of them were in Manisa city, and 510 of them in Erciyes. We sought to identify variables that contribute to euthanasia attitude, including demographics, in order to demonstrate Turkish doctors', nurses', and midwives' attitudes toward euthanasia and to compare their attitudes in this regard. The data was collected by a two-part questionnaire. The first part included questions about the health personnel; the second part comprised the euthanasia (Medical Staffs Attitude toward Euthanasia) scale. The scale was developed by the researcher to measure the attitude of healthy staff euthanasia. The SPSS was used to analyze the data. Student t-test, ANOVA, Mann Whitney U, and Kruskal Wallis were used to evaluate the data. Thep value 0.05 (95% confidence interval) was accepted as significant. In our study, professional groups are compared with all the factors but there is a significant difference only between social cost and professional groups.     

The Restricted and Unrestricted Two-Parameter Estimators

In this article, we introduce a new two-parameter estimator by grafting the contraction estimator into the modified ridge estimator proposed by Swindel (1976 Swindel , B. F. ( 1976 ). Good ridge estimators based on prior information . Commun. Statist. Theor. Meth. A5 : 1065 – 1075 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). This new two-parameter estimator is a general estimator which includes the ordinary least squares, the ridge, the Liu, and the contraction estimators as special cases. Furthermore, by setting restrictions Rβ = r on the parameter values we introduce a new restricted two-parameter estimator which includes the well-known restricted least squares, the restricted ridge proposed by Groß (2003 Groß , J. ( 2003 ). Restricted ridge estimation . Statist. Probab. Lett. 65 : 57 – 64 .[Crossref], [Web of Science ®] , [Google Scholar]), the restricted contraction estimators, and a new restricted Liu estimator which we call the modified restricted Liu estimator different from the restricted Liu estimator proposed by Kaç?ranlar et al. (1999 Kaç?ranlar , S. , Sakall?o?lu , S. , Akdeniz , F. , Styan , G. P. H. , Werner , H. J. ( 1999 ). A new biased estimator in linear regression and a detailed analysis of the widely-analysed dataset on Portland cement . Sankhya Ser. B., Ind. J. Statist. 61 : 443 – 459 . [Google Scholar]). We also obtain necessary and sufficient condition for the superiority of the new two-parameter estimator over the ordinary least squares estimator and the comparison of the new restricted two-parameter estimator to the new two-parameter estimator is done by the criterion of matrix mean square error. The estimators of the biasing parameters are given and a simulation study is done for the comparison as well as the determination of the biasing parameters.     

Tests of Multivariate Independence for Ordinal Data

Population and sample versions of Kendall and Spearman measures of association suitable for multivariate ordinal data are defined. The latter generalize the indices of dependence of Ruymgaart and van Zuijlen (1978 Ruymgaart , F. H. , van Zuijlen , M. C. A. ( 1978 ). Asymptotic normality of multivariate linear rank statistics in the non-i.i.d. case . Ann. Statist. 6 : 588 – 602 .[Crossref], [Web of Science ®] , [Google Scholar]), Joe (1990 Joe , H. ( 1990 ). Multivariate concordance . J. Multivariate Anal. 35 : 12 – 30 .[Crossref], [Web of Science ®] , [Google Scholar]), and Schmid and Schmidt (2007 Schmid , F. , Schmidt , R. ( 2007 ). Multivariate extensions of Spearman's rho and related statistics . Statist. Probab. Lett. 77 : 407 – 416 .[Crossref], [Web of Science ®] , [Google Scholar]) by allowing atoms in the underlying distribution. The representation of the proposed empirical measures as U-statistics enables to establish their asymptotic normality under general distributions. A special attention is given to tests of independence for multivariate ordinal data, where the power of the new methodologies are investigated under fixed and contiguous alternatives.     

The skew generalized t distribution as the scale mixture of a skew exponential power distribution and its applications in robust estimation

In this paper, we consider the family of skew generalized t (SGT) distributions originally introduced by Theodossiou [P. Theodossiou, Financial data and the skewed generalized t distribution, Manage. Sci. Part 1 44 (12) ( 1998), pp. 1650–1661] as a skew extension of the generalized t (GT) distribution. The SGT distribution family warrants special attention, because it encompasses distributions having both heavy tails and skewness, and many of the widely used distributions such as Student's t, normal, Hansen's skew t, exponential power, and skew exponential power (SEP) distributions are included as limiting or special cases in the SGT family. We show that the SGT distribution can be obtained as the scale mixture of the SEP and generalized gamma distributions. We investigate several properties of the SGT distribution and consider the maximum likelihood estimation of the location, scale, and skewness parameters under the assumption that the shape parameters are known. We show that if the shape parameters are estimated along with the location, scale, and skewness parameters, the influence function for the maximum likelihood estimators becomes unbounded. We obtain the necessary conditions to ensure the uniqueness of the maximum likelihood estimators for the location, scale, and skewness parameters, with known shape parameters. We provide a simple iterative re-weighting algorithm to compute the maximum likelihood estimates for the location, scale, and skewness parameters and show that this simple algorithm can be identified as an EM-type algorithm. We finally present two applications of the SGT distributions in robust estimation.     

The generalized T Birnbaum–Saunders family

In this work, we generalize the Birnbaum–Saunders distribution using the generalized t distribution alternatively to the normal distribution. The newly defined family is positively skewed and contains distributions with different kurtosis and skewness. We study its properties and special cases and demonstrate its use on some real data sets considering the maximum-likelihood estimation procedure.