A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

On a Dualization of Graphical Gaussian Models: A Correction Note

Abstract.  We correct two proofs concerning Markov properties for graphs representing marginal independence relations.     

Risk Compensation or Risk Reduction? Seatbelts,State Laws,and Traffic Fatalities*

Objective. The risk compensation hypothesis suggests that drivers enjoying greater safety will drive more recklessly and thereby impose greater risks on nonoccupants. We provide a test of the risk compensation hypothesis in the context of state seatbelt laws and belt use rates. Methods. Fixed‐effects models with policy and demographic variables are estimated using annual state data from 1985 to 2002 to test the effect of seatbelt laws and seatbelt use rates on logged fatality rates for occupants, pedestrians, motorcyclists, and all nonoccupants in separate models. Results. Contrary to the risk compensation hypothesis, the results indicate that both occupants and nonoccupants enjoy greater safety due to state mandatory use laws and increased safety belt use rates. Conclusion. Overall, seatbelt laws and the higher belt use these laws induce do not increase nonoccupant risk exposure. If anything, these laws and the accompanying increase in belt use result in safer driving behavior.     

No wonder social workers feel uncomfortable in court

The present article assesses the adversary systemper se and asks the question, Is there any place for courtroom antics and histrionics in cases involving children? Social workers are uncomfortable before the august body of thecourt, not because of any lack of education or knowledge on their part but because of the nature of the adversary process itself.     

A Review of Kyoto Protocol Adoption in Russia: Joint Implementation in Focus

Russia’s role in ‘animation’ of the Kyoto Protocol was crucial. Its initial vacillation on ratification was predominantly due to political bargaining with the EU. Domestic economic rationales [i.e. impacts of emission trading and Joint Implementation (JI) projects] were important to a much lesser extent and environmental motives did not seem to play any role in the decision. Since the Protocol entered into force, there have been significant delays in complete establishment of policy implementation frameworks, which are necessary for Russia to start benefiting from JI and emission trading. Only recently, in 2007, have GHG inventories and a national registry been established and the responsibilities for implementation of the Protocol and JI among the government departments have been distributed only to a certain extent. Some constraints hindering JI projects, such as vague legislation, an unfavourable economic climate, lack of commitment to JI projects, corruption, xenophobia, state and agency ‘capture’ still remain.      

Mandatory seat belt laws in the states. A study of fatal and severe occupant injuries

This study examines the impact of mandatory seat belt laws on fatal and incapacitating injury rates in the states. Annual data for all 50 states for the period 1975-1991 are used. Pooled time series analysis is employed. The general conclusion that emerges from this analysis is that seat belt laws significantly impact state fatal injury rates. Primary enforcement and all-seat coverage provisions appear to be particularly effective in reducing fatality rates.     

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.