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...     

Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks

Catastrophic events, such as floods, earthquakes, hurricanes, and tsunamis, are rare, yet the cumulative risk of each event occurring at least once over an extended time period can be substantial. In this work, we assess the perception of cumulative flood risks, how those perceptions affect the choice of insurance, and whether perceptions and choices are influenced by cumulative risk information. We find that participants' cumulative risk judgments are well represented by a bimodal distribution, with a group that severely underestimates the risk and a group that moderately overestimates it. Individuals who underestimate cumulative risks make more risk‐seeking choices compared to those who overestimate cumulative risks. Providing explicit cumulative risk information for relevant time periods, as opposed to annual probabilities, is an inexpensive and effective way to improve both the perception of cumulative risk and the choices people make to protect against that risk.     

Comparing the Prevalence and Organizational Distinctiveness of Faith-Based and Secular Development NGOs in Canada

Faith-based development organizations (FBOs) have been argued to deliver more cost-efficient development projects than their secular counterparts through exclusive access to faith networks, which provide predictable decentralized funding, the recruitment of volunteers, low employee salaries, and less overhead and indirect costs. To date, however, comparative analyses of religious and secular organizations have relied on a case-by-case approach, limiting the generalizability of findings. This study addresses this methodological gap by analyzing Registered Charity Information Return filings and organizational websites of 844 Canadian development NGOs to determine the proportion of FBOs and their organizational distinctiveness. The results show that FBOs comprise 40% of the Canadian NGO sector in terms of the number of organizations and their expenditures in developing countries, and are significantly less reliant on federal funding (p?<?.1), pay employees lower salaries (p?<?.01), but do not exhibit a significant difference in their expenditures on overhead and indirect costs. Thus, Canadian FBOs participation in faith networks shapes their organizational modus operandi but does not result in a low overhead alternative to secular NGOs.

     

The PALS parenting support programme: lessons learned from the evaluation of processes and outcomes

Although there has recently been a rise in parenting support programmes within the UK, only a minority of these programmes have benefited from evaluation of either outcomes or processes. This paper describes the development of the PALS programme (Parents Altogether Lending Support), reporting both on its effectiveness in improving parents' interactions with their children and on the lessons that were learned about embedding such a programme within the local community. Over the 18‐month period of the programme, a total of 17 courses were run, with 75 parents and carers (primarily mothers) participating in the programme overall. Evaluation results indicated that participants enjoyed the course and found it beneficial, particularly in terms of altering their own actions in specific ways that were able to promote better behaviour on the part of their children. Participants also valued the opportunity to share their experiences with other parents. The key lesson identified in regard to the development of parenting programmes concerned the need for the community to feel a sense of ownership for the initiative. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Volume 30

Theory and Society -