Custom Epoch Estimation for Surveys

The paper provides a method for generating epoch estimates for time series survey data, allowing for different periods of time (or even point estimates) according to user demand. The method uses a modified kriging estimator, which suppresses the contribution of sampling error variability in order to guarantee that custom epoch estimates have an interpolation property. For the veteran population variable of the American Community Survey, we utilize a simple Brownian Motion model of the population process and derive the modified kriging estimator for this case. The tuning parameters of this population model can be calibrated to the data via simple formulas. We illustrate the application of this method to the generation of point estimates of veteran population, an important objective for Veterans Affairs.     

Toward an integrated Bayesian network approach to measurement error detection and correction

In this article, the quality of data produced by national statistical institutes and by governmental institutions is considered. In particular, the problem of measurement error is analyzed and an integrated Bayesian network decision support system based on non-parametric Bayesian networks is proposed for its detection and correction. Non-parametric Bayesian networks are graphical models expressing dependence structure via bivariate copulas associated to the edges of the graph. The network structure and the misreport probability are estimated using a validation sample. The Bayesian network model is proposed to decide: (i) which records have to be corrected; (ii) the kind and amount of correction to be adopted. The proposed correction procedure is applied to the Banca d’Italia Survey on Household Income and Wealth and, specifically, the bond amounts are analyzed. Finally, the sensitivity of the conditional distribution of the true value random variable given the observed one to different evidence configurations is studied.     

大数据背景下网络调查样本的建模推断问题研究——以广义Boosted模型的倾向得分推断为例

随着大数据和网络的不断发展,网络调查越来越广泛,大部分网络调查样本属于非概率样本,难以采用传统的抽样推断理论进行推断,如何解决网络调查样本的推断问题是大数据背景下网络调查发展的迫切需求。本文首次从建模的角度提出了解决该问题的基本思路：一是入样概率的建模推断,可以考虑构建基于机器学习与变量选择的倾向得分模型来估计入样概率推断总体;二是目标变量的建模推断,可以考虑直接对目标变量建立参数、非参数或半参数超总体模型进行估计;三是入样概率与目标变量的双重建模推断,可以考虑进行倾向得分模型与超总体模型的加权估计与混合推断。最后,以基于广义Boosted模型的入样概率建模推断为例演示了具体解决方法。     

The importance of systems thinking,context, and inclusion when studying the feasibility of expanding the FoodShare (SNAP) outreach program to rural communities of Northern Wisconsin

Evaluators often neglect to question whether a program has been appropriately designed for a new context prior to a feasibility study’s commencement. In this paper, we document the results of a case study that closely examined context when determining the feasibility of implementing a FoodShare outreach program in rural northern Wisconsin. Using community-based participatory mixed methods, we examine how stakeholder engagement led to both study refinement and a more comprehensive understanding of community food security based on contextual factors and systems thinking. Lessons learned when conducting feasibility studies from this perspective are provided to improve evaluation practice.     

Towards an assessment for organizational participatory research health partnerships: A systematic mixed studies review with framework synthesis

Within the health sciences, organizational participatory research (OPR) is defined as a blend of research and action, in which academic researchers partner with health organization members. OPR is based on a sound partnership between all stakeholders to improve organizational practices. However, little research on the evaluation of OPR health partnership exists. This systematic mixed studies review sought to produce a new theoretical model that structures the evaluation of the OPR processes and related outcomes of OPR health partnerships. Six bibliographic databases were searched together with grey literature sources for OPR health partnership evaluation questionnaires. Six questionnaires were included, from which a pool of 95 OPR health partnership evaluation items were derived. The included questionnaires were appraised for the quality of their origin, development and measurement properties. A framework synthesis was performed using an existing OPR framework by organizing questionnaire items in a matrix using a hybrid thematic analysis. This led to our proposed Organizational Participatory Research Evaluation Model (OPREM) that includes three axes, Trust, Collective Learning and Sustainability (with specific dimensions) and 95 items. This model provides information to help stakeholders comprehensively structure the evaluation of their partnerships and subsequent improvement; thus, potentially helping to improve health organization practices.     

Reasons That Could Lead People to Divorce in an Evolutionary Perspective: Evidence from Cyprus

In the current research, we aimed to identify the reasons that could drive people to get a divorce. In Study 1, we employed qualitative research methods, and we identified 62 reasons that could potentially drive people to get a divorce. Using quantitative research methods, in Study 2 we classified these reasons into 7 broader factors. We found that being a harmful spouse was the most important factor for divorce, followed by incompatibility and in-law problems. We also found significant sex differences in several factors such as women indicating a higher willingness than men to divorce a harmful spouse. In addition, participants with children were less willing to divorce a harmful spouse than those who had no children. Finally, using second-order principal components analysis, we classified the 7 factors into 2 broader domains of reasons for getting a divorce.     

Paving the Way for A Normal Life: A Qualitative Study of Coping Strategies Among Iranian Divorced Women

Regarding the devastating aftermath of divorce among Iranian divorced women, which is mainly affected by sociocultural factors, this qualitative study was conducted to explore their applied strategies in reorganizing their lives. Data collection started through deep unstructured interviews followed by semistructured interviews with 18 divorced women who were chosen by purposive sampling from mental health clinics, social work centers, or available cases. Gathered data were analyzed using the qualitative content analysis method. Two main themes—behaviors of self-preservation and abstinence and struggling for balance—emerged. Subcategories were concealing the divorce, feminine self-restriction, avoidance behaviors, replacement of losses, seeking support, role development, handling the tensions, and defending oneself against the divorce failure. This study provides comprehensive knowledge of how Iranian divorced women reregulate their lives and also highlights their unique and culture-based coping strategies. Therefore, it provides specialists with a context-specific foundation for mental health care and enables them to intervene more effectively.     

“To get the word out”: LGBTQ+ Young adults’ motivations for participating in qualitative research studies

Understanding why socially marginalized individuals, such as lesbian, gay, bisexual, transgender and/or queer (LGBTQ+) people, participate in research can improve qualitative research designs, as well as social services and policies. In providing a participant-centered foundation, we interviewed 65 LGBTQ+ young adults and asked “Why are certain LGBTQ+ young adults motivated to engage in qualitative social science studies?” Many LGBTQ+ young people said they were committed to enacting social change and promoting advocacy. Participants also highlighted supporting scientific research and knowledge production. Finally, LGBTQ?+ participants engaged with research to introspectively analyze their identity development processes. These findings can facilitate access to socially vulnerable and underrepresented groups through a methodological focus on participant benefits.