Multiple comparisons in two-factor testing of psychophysical thresholds by the delta test method

We propose an algorithm of multiple comparisons in two-factor testing of psychophysical thresholds. We use logistic regression combined with guessing rate and adopt the step-down procedure with Ryan–Einot–Gabriel–Welsch (REGW) significance levels for multiple test. We test hypotheses of main effects and interaction in two-factor problem by using the delta test statistics.     

A goodness of fit test for the multilevel proportional odds model

It is essential to test the goodness of fit of the model before making inferences based on it. Multilevel modeling of ordinal categorical responses is not as developed as for continuous responses. Assessing model adequacy in terms of the goodness of fit with ordinal categorical responses is still being developed and no satisfactory tests are available so far. As a consequence of that, this study concentrates on developing such a goodness of fit test for Multilevel Proportional Odds models and to study the properties of the test.     

Combined asymmetric spatial weights matrix with application to housing prices

In this study, a combined asymmetric spatial weights matrix is proposed for capturing the unequal spatial dependence of housing prices, where the advantage of this matrix was demonstrated by a non-nested hypothesis test. To explore the heterogeneous spatial impacts of urban essential characteristics on housing prices over the eastern, central, and western regions of China, after the Lagrange multiplier and likelihood ratio tests, the spatial Durbin model using the proposed weights matrix was applied to each region. The estimation results showed that the direct impacts of college and new employment were significantly negative in the eastern region, but not significant in the central and western regions. By contrast, the direct impacts of hospitals and scenic spots were significantly positive in eastern China, but not significant in central and western China. In addition, the indirect impacts of the four variables were not significant in the three regions. These results suggest that in eastern China, the government may increase the requirements for using medical resources and close tourist attractions in a single city to cool down the skyrocketing housing prices in this area.     

A weighted Harrell–Davis distance test with applications to censored data

Consider the standard treatment-control model with a time-to-event endpoint. We propose a novel interpretable test statistic from a quantile function point of view. The large sample consistency of our estimator is proven for fixed bandwidth values theoretically and validated empirically. A Monte Carlo simulation study also shows that given small sample sizes, utilization of a tuning parameter through the application of a smooth quantile function estimator shows an improvement in efficiency in terms of the MSE when compared to direct application of classic Kaplan–Meier survival function estimator. The procedure is finally illustrated via an application to epithelial ovarian cancer data.     

Child‐Care Instability and Behavior Problems: Does Parenting Stress Mediate the Relationship?

Child‐care instability is associated with more behavior problems in young children, but the mechanisms of this relationship are not well understood. Theoretically, this relationship is likely to emerge, at least in part, because care instability leads to increased parenting stress. Moreover, low socioeconomic status and single‐mother families may be more vulnerable to the effects of instability. This study tested these hypotheses using data from the Fragile Families and Child Wellbeing study (N = 1,675) and structural equation modeling. Three types of child‐care instability were examined: long‐term instability, multiplicity, and needing to use back‐up arrangements. Overall, findings showed little evidence that parenting stress mediated the associations between care instability and child behavior problems among the full sample. Among single‐mother and low‐income families, however, needing to use back‐up arrangements had small positive associations with parenting stress, which partially mediated the relationship between that type of care instability and child externalizing behavior problems.     

College students coping with interpersonal stress: Examining a control-based model of coping

Objective: The ways that college students cope with stress, particularly interpersonal stress, may be a critical factor in determining which students are at risk for impairing mental health disorders. Using a control-based model of coping, the present study examined associations between interpersonal stress, coping strategies, and symptoms. Participants: A total of 135 undergraduate students from 2 universities. Methods: Interpersonal stress, coping strategies, depression, anxiety, and somatization were assessed via self-report. Results: Students reporting more interpersonal stress reported more depression, anxiety, and somatization, and they reported less use of engagement coping strategies and greater use of disengagement coping strategies. Engagement coping strategies accounted for a significant portion of the association between interpersonal stress and mental health symptoms. Unexpectedly, coping strategies did not moderate the association between stress and mental health symptoms. Conclusion: Interventions designed to improve students' coping strategies may be an effective way to reduce mental health problems on college campuses.     

Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression

Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters and their uncertainty estimates depend upon the underlying error variance structure in the model. Typically, a priori the researcher would not know if the error variances are homoscedastic (i.e., constant across dose) or if they are heteroscedastic (i.e., the variance is a function of dose). Motivated by this concern, in this paper we introduce an estimation procedure based on preliminary test which selects an appropriate estimation procedure accounting for the underlying error variance structure. Since outliers and influential observations are common in toxicological data, the proposed methodology uses M-estimators. The asymptotic properties of the preliminary test estimator are investigated; in particular its asymptotic covariance matrix is derived. The performance of the proposed estimator is compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using a data set obtained from the National Toxicology Program.     

The Impact of Social Connectedness and Internalized Transphobic Stigma on Self-Esteem Among Transgender and Gender Non-Conforming Adults

The transgender and gender non-conforming (TGNC) community continues to represent a notably marginalized population exposed to pervasive discrimination, microaggressions, and victimization. Congruent with the minority stress model, TGNC individuals persistently experience barriers to wellbeing in contemporary society; however, research uncovering resilience-based pathways to health among this population is sparse. This study aimed to explore the impact and interaction between internalized transphobic stigma and a potential buffer against minority stress—social connectedness—on the self-esteem of TGNC identified adults. Data were collected from 65 TGNC identified adults during a national transgender conference. Multiple regression analysis reveals that self-esteem is negatively impacted by internalized transphobia and positively impacted by social connectedness. Social connectedness did not significantly moderate the relationship between internalized transphobia and self-esteem. Micro and macro interventions aimed at increasing social connectedness and decreasing internalized transphobic stigma may be paramount for enhancing resiliency and wellbeing in the TGNC community.     

On some aspects of a generalized alternative zero-inflated logarithmic series distribution

Here, we consider a generalized form of the alternative zero-inflated logarithmic series distribution of Kumar and Riyaz (J. Statist. Comp. Simul., 2015) and study some of its important aspects. The parameters of the distribution are estimated by the method of maximum likelihood and some test procedures are developed for testing the significance of the additional parameter of the model. All these estimation and testing procedures are illustrated with the help of certain real life datasets. A simulation study is also carried out for assessing the performance of the estimators.     

Comparison of preliminary test estimators based on generalized order statistics from proportional hazard family using Pitman measure of closeness

In this article, based on generalized order statistics from a family of proportional hazard rate model, we use a statistical test to generate a class of preliminary test estimators and shrinkage preliminary test estimators for the proportionality parameter. These estimators are compared under Pitman measure of closeness (PMC) as well as MSE criteria. Although the PMC suffers from non transitivity, in the first class of estimators, it has the transitivity property and we obtain the Pitman-closest estimator. Analytical and graphical methods are used to show the range of parameter in which preliminary test and shrinkage preliminary test estimators perform better than their competitor estimators. Results reveal that when the prior information is not too far from its real value, the proposed estimators are superior based on both mentioned criteria.