Introduction of a new measure for detecting poor fit due to omitted nonlinear terms in SEM

The model chi-square that is used in linear structural equation modeling compares the fitted covariance matrix of a target model to an unstructured covariance matrix to assess global fit. For models with nonlinear terms, i.e., interaction or quadratic terms, this comparison is very problematic because these models are not nested within the saturated model that is represented by the unstructured covariance matrix. We propose a novel measure that quantifies the heteroscedasticity of residuals in structural equation models. It is based on a comparison of the likelihood for the residuals under the assumption of heteroscedasticity with the likelihood under the assumption of homoscedasticity. The measure is designed to respond to omitted nonlinear terms in the structural part of the model that result in heteroscedastic residual scores. In a small Monte Carlo study, we demonstrate that the measure appears to detect omitted nonlinear terms reliably when falsely a linear model is analyzed and the omitted nonlinear terms account for substantial nonlinear effects. The results also indicate that the measure did not respond when the correct model or an overparameterized model were used.     

Die intra-individuelle Stabilität gesellschaftlicher Wertorientierungen

In empirical social research very little is known about the internal stability of social value orientations. The main reason for this is a shortage of long-time panel studies including usable value indicators. Beyond this background we analyse the German Socio-Economic Panel (SOEP) which enables us to examine the internal stability of Inglehart’s postmaterialism across a time span of at least twelve years. By using multi-level-models for panel data we can demonstrate the existence of cohort effects as well as life cycle effects among the two youngest birth cohorts and among respondents with higher education.     

Power kurtosis transformations: Definition, properties and ordering

Summary Heavy tail distributions can be generated by applying specific non-linear transformations to a Gaussian random variable. Within this work we introduce power kurtosis transformations which are essentially determined by their generator function. Examples are theH-transformation of Tukey (1960), theK-transformation of MacGillivray and Cannon (1997) and theJ-transformation of Fischer and Klein (2004).Furthermore, we derive a general condition on the generator function which guarantees that the corresponding transformation is actually tail-increasing. In this case the exponent of the power kurtosis transformation can be interpreted as a kurtosis parameter. We also prove that the transformed distributions can be ordered with respect to the partial ordering of van Zwet (1964) for symmetric distributions.     

Confidence Bands for the Difference of Two Survival Curves Under Proportional Hazards Model

A common approach to testing for differences between the survival rates of two therapies is to use a proportional hazards regression model which allows for an adjustment of the two survival functions for any imbalance in prognostic factors in the comparison. When the relative risk of one treatment to the other is not constant over time the question of which therapy has a survival advantage is difficult to determine from the Cox model. An alternative approach to this problem is to plot the difference between the two predicted survival functions with a confidence band that provides information about when these two treatments differ. Such a band will depend on the covariate values of a given patient. In this paper we show how to construct a confidence band for the difference of two survival functions based on the proportional hazards model. A simulation approach is used to generate the bands. This approach is used to compare the survival probabilities of chemotherapy and allogeneic bone marrow transplants for chronic leukemia.     

Sexual orientation: a multi-variable dynamic process

Theory and research concerning sexual orientation has been restricted in its scope and influence by the lack of clear and widely accepted definitions of terms like heterosexual, bisexual, and homosexual. In an attempt to better demarcate and understand the complexities of human sexual attitudes, emotions, and behavior, the Klein Sexual Orientation Grid (KSOG) was developed and administered. The KSOG is composed of seven variables that are dimensions of sexual orientation, each of which is rated by the subject as applying to the present, past, or ideal. Analysis of the data from subjects who filled out the KSOG in Forum Magazine indicated that the instrument was a reliable and valid research tool which took into consideration the multi-variable and dynamic aspects of sexual orientation.     

Impediments to Academic Performance of Bisexual College Students

Abstract

Objective: To investigate health-related impediments to academic success for bisexual college students. Participants: Respondents to the Fall 2011 American College Health Association–National College Health Assessment II (ACHA-NCHA II) survey who self-identified as bisexual, heterosexual, gay, or lesbian. Methods: Secondary analyses of the ACHA-NCHA II data were conducted to compare the experiences of bisexual students with both each other (bisexual men and bisexual women) and those of their nonbisexual counterparts (heterosexual and gay/lesbian students). Results: Bisexual college students are a large and distinct sexual minority group. On all measures with the exception of discrimination, bisexual college students reported the strongest threats to academic success of all sexual orientations. Conclusions: Given the unique impediments for bisexual students, college health professionals should consider specifically addressing needs for bisexual students, bisexual women in particular.     

Primary Care Screening of Depression and Treatment Engagement in a University Health Center: A Retrospective Analysis

Abstract

Objectives: This retrospective study analyzed a primary care depression screening initiative in a large urban university health center. Depression detection, treatment status, and engagement data are presented. Participants: Participants were 3,713 graduate and undergraduate students who presented consecutively for primary care services between January and April 2006. Methods: A standardized 2-tiered screening approach for an inception cohort of students utilizing primary services. Primary care providers were trained to triage students with depressive symptoms. Results: Six percent of participants had clinically significant depressive symptoms (CSD). Severe depressive symptoms were found in less than 1.0% of participants. Male rates of severe depressive symptoms were more than double that of females. Only 35.7% of untreated depressed participants started treatment within 30 days following identification. Conclusions: Systematic primary care depression screening in a college health center is a promising approach to identify untreated students with depression. More study is needed to improve rates of treatment engagement.     

Self-generated motives for gambling in two population-based samples of gamblers

In the present study, self-generated responses to a question regarding reasons for gambling from two epidemiological surveys were combined and placed into another earlier motivational model for alcohol use, adapted for gambling. Of the 3601 reasons, 954 could be categorised into the model's categories: (a) coping motives (internal, negative reinforcement); (b) enhancement motives (internal, positive reinforcement); and (c) social motives (external, positive reinforcement). Results indicate that coping gamblers experienced greater gambling severity and psychopathology, enhancement gamblers were most likely to gamble while intoxicated and social gamblers were more likely to choose socially-related gambling. An examination of remaining motives suggests additional categories may be warranted – specifically financial and charitable reasons. These findings offer some support for the model; however, it may need to be expanded to account for other motives. The study highlights the advantages and limitations of using self-generated reasons to study gambling motivation.