Identity and integration: The roles of relationship and retention in nonprofit mergers

Prior research suggests that nonprofits are flexible and possess multiple identities, although we know less about how transformative changes, such as mergers, shape nonprofit identity. This qualitative study draws upon in‐depth interviews from 13 nonprofit merger cases to explore factors that influence postmerger identity and integration. In particular, we focus on the roles of organizational similarity and relationships, program and personnel retention, and rebranding. Ultimately, we derive a typology of postmerger integration in nonprofits and suggest that postmerger identity may be classified in terms of absorption, preservation, or creation. Implications for nonprofit leaders are discussed.     

Topics on Dynamic Panel Data Models with Random Effects Using Semi-Parametric Bayesian Approach

A common assumption in fitting panel data models is normality of stochastic subject effects. This can be extremely restrictive, making vague most potential features of true distributions. The objective of this article is to propose a modeling strategy, from a semi-parametric Bayesian perspective, to specify a flexible distribution for the random effects in dynamic panel data models. This is addressed here by assuming the Dirichlet process mixture model to introduce Dirichlet process prior for the random-effects distribution. We address the role of initial conditions in dynamic processes, emphasizing on joint modeling of start-up and subsequent responses. We adopt Gibbs sampling techniques to approximate posterior estimates. These important topics are illustrated by a simulation study and also by testing hypothetical models in two empirical contexts drawn from economic studies. We use modified versions of information criteria to compare the fitted models.     

Regularization in dynamic random-intercepts models for analysis of longitudinal data

This paper addresses the problem of simultaneous variable selection and estimation in the random-intercepts model with the first-order lag response. This type of model is commonly used for analyzing longitudinal data obtained through repeated measurements on individuals over time. This model uses random effects to cover the intra-class correlation, and the first lagged response to address the serial correlation, which are two common sources of dependency in longitudinal data. We demonstrate that the conditional likelihood approach by ignoring correlation among random effects and initial responses can lead to biased regularized estimates. Furthermore, we demonstrate that joint modeling of initial responses and subsequent observations in the structure of dynamic random-intercepts models leads to both consistency and Oracle properties of regularized estimators. We present theoretical results in both low- and high-dimensional settings and evaluate regularized estimators' performances by conducting simulation studies and analyzing a real dataset. Supporting information is available online.     

The effect of acupressure on the initiation of labor: A randomized controlled trial

Background

Induction of labor is a common obstetric procedure. Acupressure is a natural method that is used for inducing uterine contractions. Nevertheless, few studies have examined the impact of acupressure on the induction of labor.

Exercise training in thermo-mineral spring water has beneficial effects on hemodynamic and health-related factors in young-older hypertensive women: A randomized control trial

ABSTRACT

The aim of the study was to evaluate the effects of an 8-week aerobic training in mineral geothermal water on hemodynamic variables, VO_2max, and body composition in sedentary hypertensive women. Twenty postmenopausal women (58.55 ± 3.28 years) were divided into an exercise group (2 days/week, 30–40 minutes, 60%–75% of HR_max) and control group. Compared to the control group, a signi?cant reduction in systolic blood pressure, heart rate, rate pressure product, body fat percent, and a signi?cant improvement in VO_2max values was found. Aerobic training in thermo-mineral spring water is a safe and effective training modality in the young-older hypertensive population.     

A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension

In this paper, we investigate estimation methods to deal with situations where random intercepts are associated to time-varying covariates in the context of linear mixed models. First, a review of previous ways to deal with this so-called endogeneity issue is presented, then a new method based on shared random effects is proposed. Simulation studies and an empirical example are utilized to assess the performance of our proposed method. It is shown that our new approach is more efficient than most competitors and is robust to the misspecification of the random-effects distributions.