A goodness of fit test for multilevel survival data

No satisfactory goodness of fit test is available for multilevel survival data which occur when survival data are clustered or hierarchical in nature. Hence the aim of this research is to develop a new goodness of fit test for multilevel survival data and to examine the properties of the newly developed test. Simulation studies were carried out to evaluate the type ? error and the power. The results showed that the type I error holds for every combination tested and that the test is powerful against the alternative hypothesis of nonproportional hazards for all combinations tested.     

Bivariate versus univariate ordinal categorical data with reference to an ophthalmologic study

The Wisconsin Epidemiologic Study of Diabetic Retinopathy is a population-based epidemiological study carried out in Southern Wisconsin during the 1980s. The resulting data were analysed by different statisticians and ophthalmologists during the last two decades. Most of the analyses were carried out on the baseline data, although there were two follow-up studies on the same population. A Bayesian analysis of the first follow-up data, taken four years after the baseline study, was carried out by Angers and Biswas [Angers, J.-F. and Biswas, A., 2004, A Bayesian analysis of the four-year follow-up data of theWisconsin epidemiologic study of diabetic retinopathy. Statistics in Medicine, 23, 601–615.], where the choice of the best model in terms of the covariate inclusion is done, and estimates of the associated covariate effects were obtained using the baseline data to set the prior for the parameters. In the present article we consider an univariate transformation of the bivariate ordinal data, and a parallel analysis with the much simpler univariate data is carried out. The results are then compared with the results of Angers and Biswas (2004). In conclusion, our analyses suggest that the univariate analysis fails to detect features of the data found by the bivariate analysis. Even an univariate transformation of our data with quite high correlation with both left and right eyes is inadequate.     

Introductory Statistics Textbooks and the GAISE Recommendations

The six recommendations made by the Guidelines for Assessment and Instruction in Statistics Education (GAISE) committee were first communicated in 2005 and more formally in 2010. In this article, 25 introductory statistics textbooks are examined to assess how well these textbooks have incorporated the three GAISE recommendations most relevant to implementation in textbooks (statistical literacy and thinking; use of real data; stress concepts over procedures). The implementation of another recommendation (using technology) is described but not assessed. In general, most textbooks appear to be adopting the GAISE recommendations reasonably well in both exposition and exercises. The textbooks are particularly adept at using real data, using real data well, and promoting statistical literacy. Textbooks are less adept—but still rated reasonably well, in general—at explaining concepts over procedures and promoting statistical thinking. In contrast, few textbooks have easy-usable glossaries of statistical terms to assist with understanding of statistical language and literacy development. Supplementary materials for this article are available online.     

浅议高校财务信息化的安全问题

随着计算机的发展和信息化的普及，各个行业都不断地在改革和创新，财务行业亦是不落人后。财务信息化改变了传统的会计模式，加快了效率，降低了差错率，提高了数据处理能力，适应当前前经济社会发展的需要。但与此同时，复杂的互联网环境与财务信息系统特有的性质也带来了新的隐患，直接影响账务安全，威胁整个财务行业的发展。因此，探讨软硬件防护对安全管理的意义有助于高校计划财务处信息化建设工作。     

Least squares estimation of varying‐coefficient hazard regression with application to breast cancer dose‐intensity data

To enhance modeling flexibility, the authors propose a nonparametric hazard regression model, for which the ordinary and weighted least squares estimation and inference procedures are studied. The proposed model does not assume any parametric specifications on the covariate effects, which is suitable for exploring the nonlinear interactions between covariates, time and some exposure variable. The authors propose the local ordinary and weighted least squares estimators for the varying‐coefficient functions and establish the corresponding asymptotic normality properties. Simulation studies are conducted to empirically examine the finite‐sample performance of the new methods, and a real data example from a recent breast cancer study is used as an illustration. The Canadian Journal of Statistics 37: 659–674; 2009 © 2009 Statistical Society of Canada     

Using Multilevel Statistical Models in Social Work Intervention Research

ABSTRACT

Statistical analyses of data from a classroom-based study illustrate the need to account for intra-class clustering in studies involving schools, classrooms, and other higher order units of analysis. Students were clustered in homerooms that were assigned to intervention and comparison conditions. Standard multiple linear regression analysis yielded a significant group effect but incorrectly ignored intra-cluster response correlations. A multilevel model appropriately accounting for the dependency among responses in the same cluster yielded a nonsignificant group effect. Implications for the analysis of intervention research data are discussed.     

Adolescents,Online Marketing and Privacy: Predicting Adolescents’ Willingness to Disclose Personal Information for Marketing Purposes

The present study aims at exploring which factors predict the willingness of adolescents to disclose personal information in response to online marketing requests. Our analyses show that especially privacy concerns and perceived benefits explain a considerable portion of variance in both willingness to disclose profile data (e.g. age, hobbies, favourite products) and contact data (e.g. phone number, e‐mail address, home address). An interesting interrelationship was found between profile data and contact data disclosure. Contrary to our expectations, parental mediation strategies were only a weak predictor of teenagers’ willingness to disclose contact information. Policy implications that emerge from the central findings of this study are discussed.     

On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

Efficacy of Statistical Outlier Analysis for Monitoring Quality of Care

Researchers have proposed that hospitals with excessive statistically unexplained mortality rates are more likely to have quality-of-care problems. The U.S. Health Care Financing Administration currently uses this statistical “outlier” approach to screen for poor quality in hospitals. Little is known, however, about the validity of this technique, since direct measures of quality are difficult to obtain. We use Monte Carlo methods to evaluate the performance of the outlier technique as parameters of the true mortality process are varied. Results indicate that the screening ability of the technique may be very sensitive to how widespread quality-related mortality is among hospitals but insensitive to other factors generally thought to be important.     

Intimate Violence in Lesbian Relationships

This paper describes the findings of a survey of 1109 lesbians who attended the Women's Music Festival held in Michigan in carly August 1985. The primary objectives of the study were to document the incidence of domestic violence in a non-random sample of lesbian relationships; to identify and describe the types of domestic violence experienced and/or perpetrated; and to ascertain thc availability and accessibility of community helping resources to survivors and perpetrators after an abusive episode. Comparisons with domestic violence in heterosexual relationships are also made, followed by a discussion on the research and practice implications of the findings.