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...     

Catering to sex,sexual, and gender diversity: An exploratory study on the effects of LGBTI awareness training on aged care staff in Tasmania,Australia

The Australian National LGBTI Ageing and Aged Care Strategy seeks to address the lack of recognition of older lesbian, gay, bisexual, transgender, and intersex (LGBTI) adults living in aged care. Awareness training for aged care staff forms a crucial part of this strategy, but the impact of such educational programs are yet to be examined. In this article, we examine the effects of LGBTI awareness training on staff working in an Australian aged care facility. These staff perceived the awareness training as valuable, but the outcomes from it were limited. Therefore, we indicate changes that are necessary to support the translation of training into practice.     

Changing Frameworks in Attitudes Toward Abortion

For more than two decades, legal abortion has been the subject of heated political debate and adversarial social movement activity; however, national polls have shown little change in aggregate levels of support for abortion. This analysis examines how the determinants of abortion attitudes have changed between 1977 and 1996, using data from the General Social Surveys. While in early time periods, whites were more approving of abortion than blacks, that pattern had reversed by the late 1980s. After controlling for other factors, older people are more accepting of abortion throughout the two decades, while gender is generally unrelated to abortion views. Catholic religion weakens slightly as a predictor of abortion attitudes, while religious fundamentalism and political liberalism increase in explanatory power. The associations between attitudinal correlates and abortion approval also change over this time period. Religiosity becomes a less powerful predictor of abortion attitudes, while respondents' attitude toward sexual freedom and belief in the sanctity of human life increase in their predictive power. Support for gender inequality remains a weak but stable predictor of abortion attitudes. This pattern of results suggests that the public is influenced more by the pro-life framework of viewing abortion than by the pro-choice perspective.     

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.     

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.