GMM in linear regression for longitudinal data with multiple covariates measured with error

Griliches and Hausman 5 Griliches, Z. and Hausman, J. A. 1986. Errors in variables in panel data. J. Econometrics, 32: 93–118. [Crossref], [Web of Science ®] [Google Scholar] and Wansbeek 11 Wansbeek, T. J. 2001. GMM estimation in panel data models with measurement error. J. Econometrics, 104: 259–268. [Crossref], [Web of Science ®] [Google Scholar] proposed using the generalized method of moments (GMM) to obtain consistent estimators in linear regression models for longitudinal data with measurement error in one covariate, without requiring additional validation or replicate data. For usefulness of this methodology, we must extend it to the more realistic situation where more than one covariate are measured with error. Such an extension is not straightforward, since measurement errors across different covariates may be correlated. By a careful construction of the measurement error correlation structure, we are able to extend Wansbeek's GMM and show that the extended Griliches and Hausman's GMM is equivalent to the extended Wansbeek's GMM. For illustration, we apply the extended GMM to data from two medical studies, and compare it with the naive method and the method assuming only one covariate having measurement error.     

Variability explained by covariates in linear mixed‐effect models for longitudinal data

Variability explained by covariates or explained variance is a well‐known concept in assessing the importance of covariates for dependent outcomes. In this paper we study R² statistics of explained variance pertinent to longitudinal data under linear mixed‐effect models, where the R² statistics are computed at two different levels to measure, respectively, within‐ and between‐subject variabilities explained by the covariates. By deriving the limits of R² statistics, we find that the interpretation of explained variance for the existing R² statistics is clear only in the case where the covariance matrix of the outcome vector is compound symmetric. Two new R² statistics are proposed to address the effect of time‐dependent covariate means. In the general case where the outcome covariance matrix is not compound symmetric, we introduce the concept of compound symmetry projection and use it to define level‐one and level‐two R² statistics. Numerical results are provided to support the theoretical findings and demonstrate the performance of the R² statistics. The Canadian Journal of Statistics 38: 352–368; 2010 © 2010 Statistical Society of Canada     

North Americans' Attitudes Toward Illegal Drugs

Public opinion polls conducted from 1969 to 2003 found a variety of opinions on the use, possession, and legalization of marijuana. Public opinion about legalizing marijuana use is increasing, but it is also increasing toward harsher penalties for those who possess a small amount of marijuana. Public opinion regarding the legalization of illegal drugs appears to be influenced by the times. The majority of Americans increasingly believe that the country has made some progress in dealing with the problems of illegal drugs, but Americans are also reporting more difficulty within their families related to marijuana. This article examines trends based in public opinion polls on the use of marijuana in the United States and Canada and discusses the social and political history of marijuana and the biophysical effects, medical uses, definitions, and previous research related to marijuana.     

Monitoring Optimism in South Africa

The last two decades have been the most crucial and eventful ones in South Africa's history. During this time, the empirical research and knowledge provided by opinion polls yielded much-needed insight into the grass roots of a society in transition, providing an instrument with which to measure the political climate, to observe trends and developments, and to give input into the decision-making process of companies and political parties. Although the process of change and political transition still remains difficult to define properly, this article will provide some insight into the attitudes, perceptions and values of the South African public, by giving attention to trends that have transpired over the years. Special attention is devoted to perceptions on pertinent issues such as the mood in the country, optimism, economic well-being, social harmony and trust – all essential elements in an emerging democracy. Extensive use is made of data and findings of Markinor's bi-annual Socio-Political Trends surveys, the World Values Studies and the annual Gallup End-of-Year Poll.     

Evaluating systems change in a juvenile justice reform initiative

Evaluating comprehensive, interagency initiatives to reform human services systems presents substantial challenges to traditional research models. Outcomes are observed at the system level rather than the individual level, and the validity of study results may be challenged on a variety of dimensions, particularly small sample sizes and measurement error. We report the results of a cross-site evaluation of the first phase of Reclaiming Futures, a five-year effort to improve services and interventions for justice-involved youth in 10 communities across the United States. We present the evaluation findings and discuss implications for similar research endeavors. The methods used in this study may be useful for other system-level evaluation efforts. A social network analysis analyzes changes in the size, density, and cohesiveness of stakeholder networks. Bivariate models test for associations between Reclaiming Futures implementation and key stakeholder perceptions of effective system change. Multivariate models are used to explore selection effects on item response. In general, we find positive correlations between successful implementation of Reclaiming Futures and indicators of effective and efficient system change.     

Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

The Impact of Childhood Sexual Abuse on Later Sexual Victimization among Runaway Youth

Path analysis was used to investigate the impact of childhood sexual abuse on later sexual victimization among 372 homeless and runaway youth in Seattle. Young people were interviewed directly on the streets and in shelters by outreach workers in youth service agencies. High rates of both childhood sexual abuse and street sexual victimization were reported, with females experiencing much greater rates compared with their male counterparts. Early sexual abuse in the home increased the likelihood of later sexual victimization on the streets indirectly by increasing the amount of time at risk, deviant peer affiliations, participating in deviant subsistence strategies, and engaging in survival sex. These findings suggest that exposure to dysfunctional and disorganized homes place youth on trajectories for early independence. Subsequently, street life and participation in high‐risk behaviors increases their probability of sexual victimization.