The Social-Entrepreneurship Advantage: An Experimental Study of Social Entrepreneurship and Perceptions of Nonprofit Effectiveness

A common assertion in the nonprofit literature is that nonprofit organizations can become more efficient, effective, and sustainable by embracing social entrepreneurship in their operational and strategic posture. In this article, we examine whether the mere label of social entrepreneurship results—with no actual organizational differences—in an increase in positive attributions associated with a nonprofit organization, an effect we call the social entrepreneurship bias. We experimentally test for the existence of a social entrepreneurship bias by examining how the label of social entrepreneurship alters how people judge a nonprofit’s effectiveness and decide how to allocate scarce donation funds.

     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

The identification of logistic regression models with errors in the variables

The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.     

An Interview with Joyce Edward: Exemplary Clinician, Advocate, and Scholar

Over the years, noteworthy social workers have been interviewed for the Clinical Social Work Journal. This article features an interview with Joyce Edward who is recognized for her many extraordinary contributions to clinical social work. Joyce has co-written or co-edited three exceptional books for the social work clinician, she has been an esteemed teacher and a vocal activist for quality mental health care. In this interview Joyce reflects on family influences, her work as a social caseworker, the psychoanalytic luminaries with whom she trained, her concerns about the clinical education of today's social work students, and finally, her perspective on managed mental health care.     

Adolescent Protective Factors Promoting Resilience in Young Adults at Risk for Depression

In a longitudinal, community-based study, adolescent protective factors for those at risk for depression were identified that were associated with resilient outcomes in young adulthood. For those with childhood risk factors for major depression, significant protective factors included family cohesion, positive self appraisals, and good interpersonal relations. Findings may help inform the development of prevention and treatment programs for adolescents vulnerable to depression. Implications for future research and clinical practice are discussed.