The challenges of inclusive education in Lebanon

This article reports on a study conducted in Lebanon by four non-governmental organizations, primarily on the topic of inclusion of people with disabilities in education, with a secondary focus on inclusion in employment. This article reports on some of the findings of the assessment process that was four months in duration and aimed, through interviews and focus groups, to identify available information, current policies and legislation, main stakeholders and existing programmes. Findings of the assessment generated themes that are unique to each of the two groups: parents and children, and educators. However, there are some common themes, such as a perceived need for raising awareness on disability issues and a perceived lack of adequate teacher training. The article concludes by arguing for change efforts on various levels to support inclusion: awareness-raising; policy change; capacity-building; and community-building.     

Issues in applying recent CPMP ‘Points to Consider’ and FDA guidance documents with biostatistical implications

The International Conference on Harmonisation guideline ‘Statistical Principles for Clinical Trials’ was adopted by the Committee for Proprietary Medicinal Products (CPMP) in March 1998, and consequently is operational in Europe. Since then more detailed guidance on selected topics has been issued by the CPMP in the form of ‘Points to Consider’ documents. The intent of these was to give guidance particularly to non‐statistical reviewers within regulatory authorities, although of course they also provide a good source of information for pharmaceutical industry statisticians. In addition, the Food and Drug Administration has recently issued a draft guideline on data monitoring committees. In November 2002 a one‐day discussion forum was held in London by Statisticians in the Pharmaceutical Industry (PSI). The aim of the meeting was to discuss how statisticians were responding to some of the issues covered in these new guidelines, and to document consensus views where they existed. The forum was attended by industry, academic and regulatory statisticians. This paper outlines the questions raised, resulting discussions and consensus views reached. It is clear from the guidelines and discussions at the workshop that the statistical analysis strategy must be planned during the design phase of a clinical trial and carefully documented. Once the study is complete the analysis strategy should be thoughtfully executed and the findings reported. Copyright © 2003 John Wiley & Sons, Ltd.     

刻意创新

我们大多数人都认同创新是成长的关键途径。问题是如何创新?许多企业依靠突发机遇。也就是说,他们指望某个人提出产品或服务方面的点子,然后从中获利。然而有些时候,企业必须发掘比以往更多的创意,并先于竞争对手将创意化为切实可行的产品与服务。此时,企业便不能再依靠机缘巧合了。我们需要可持续、可重复的创新方法。     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

Evaluating the Use of Spatial Covariance Structures in the Analysis of Cardiovascular Imaging Data

This article investigates the choice of working covariance structures in the analysis of spatially correlated observations motivated by cardiac imaging data. Through Monte Carlo simulations, we found that the choice of covariance structure affects the efficiency of the estimator and power of the test. Choosing the popular unstructured working covariance structure results in an over-inflated Type I error possibly due to a sample size not large enough relative to the number of parameters being estimated. With regard to model fit indices, Bayesian Information Criterion outperforms Akaike Information Criterion in choosing the correct covariance structure used to generate data.     

Effects of a single-lesson tobacco prevention curriculum on knowledge, skill identification and smoking intention

One in five students report experimenting with tobacco before the age of 13 and most prevention efforts take place in the school setting. This study measures the effect of a single-lesson tobacco prevention curriculum, conducted by a health education center, focusing on knowledge of tobacco, ability to identify refusal techniques, and intent not to smoke. Data were collected, via electronic keypads, from students visiting a non-school, health education center in Michigan (n = 704 intervention and 85 comparison). Contingency table Chi-squared tests and t-tests demonstrated that a single lesson can improve general knowledge and ability to identify appropriate refusal techniques. Improvement in intent not to smoke was not significant because both groups had very high intent prior to implementation. Similar to results from other programs, multivariate logistic regression of gender, general knowledge, and skill identification revealed that only the skill variable was associated with intent not to smoke at pretest. Recommendations are given for further research and for designing more effective curricula or programs.     

An Evaluation of Staff Preference for Graphic Characteristics

The purpose of the current study was to assess staff preference for how data were displayed on graphs. Specifically, preference for line versus bar graphs was assessed, as well as preference for data displayed as one date in time versus multiple dates showing performance trends. A secondary purpose of the study was to assess staff comprehension of the data presented across different graphic displays. Participants included 60 entry-level direct care staff and 25 seasoned therapists. Therapists had more advanced training in applied behavior analysis than the direct care staff. The vast majority of direct care staff preferred data depicted as a bar graph versus data depicted as a line graph, even preferring a single bar graph over a time-series line graph. The therapists preferred time-series line graphs to bar graphs. Most staff demonstrated understanding of the data, regardless of how it was depicted.