Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Informal Work in Nonmetropolitan Pennsylvania1

Abstract It is well recognized that the informal economy—unregulated economic activities that generate real or in-kind income—features prominently in the day-to-day lives of many in the developing world. Researchers have begun to explore the informal economy in developed countries but this work has focussed primarily on urban areas to the neglect of rural areas. In this paper the nature and correlates of informal work in nonmetropolitan Pennsylvania are described through an analysis of survey data on 505 families. Results indicate that participation in informal activities is widespread, is not more typical of the poor, does not contribute greatly to family income on average but does help many poor families weather difficult economic times, is both economically and noneconomically motivated, and, net of other sociodemographic variables, is positively related to rurality of residence and formal labor supply.     

Small Town in Mass Society Revisited1

Abstract The case study of a small New York town that dramatized the thesis that the secular expansion of macro forces—urbanization, industrialization, bureaucratization—has permanently reduced the autonomy of all small communities is an example of a special type of discovery/persuasion strategy in the social sciences: the “opposition case study.” In contrast to the more rigorous “competitive test” or the atheoretical “negative case,” opposition case studies confront the dominant perspective with a qualitative illustration of a new theory in the context of a zero-sum game. When they are successful, opposition cases meet four criteria: the dominant view is immediately rendered obsolete; the origin of the new idea supports its plausibility; the new perspective is shown to be testable; and the new perspective quickly generates new lines of research. Small Town in Mass Society meets the first criterion, and may have been heuristic, but its probable origin in populist ideology undermines its testability.     

Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.     

The Impact of Question and Respondent Characteristics on Comprehension and Mapping Difficulties

Behavior coding is one technique researchers use to detect problemsin survey questions, but it has been primarily explored as apractical tool rather than a source of insight into the theoreticalunderstanding of the cognitive processes by which respondentsanswer survey questions. The latter is the focus of the currentinvestigation. Using data from a large study in which face-to-faceinterviews were taped and extensive behavior coding was done,we tested whether sets of respondent behavior codes could beused to distinguish respondent difficulties with comprehensionof the question from difficulties associated with mapping ajudgment onto the response format provided, and whether characteristicsof the survey questions and respondents could be used to predictwhen and for whom such difficulties would occur. Sets of behaviorcodes were identified that reflected comprehension and mappingdifficulties, and these two types of difficulties were associatedwith different question and respondent characteristics. Thisevidence suggests that behavior coding shows promise as a toolfor researchers studying the cognitive processes involved inanswering survey questions.     

Goal Ambiguity and Organizational Performance in U.S. Federal Agencies

In spite of numerous observations that government organizationshave high levels of organizational goal ambiguity that exertmajor influences on their other characteristics, few researchershave measured goal ambiguity and tested these frequent assertions.In previous research, we developed measures of four dimensionsof goal ambiguity: mission comprehension ambiguity, directivegoal ambiguity, evaluative goal ambiguity, and priority goalambiguity. Confirming hypotheses developed from the literatureon public organizations, the latter three variables showed relationsto such organizational characteristics as organizational age,financial publicness (proportion of funding from governmentallocations), and regulatory status. This article reports asecond analytical step of examining the relations between thegoal ambiguity dimensions and indicators of organizational performancebased on responses to the 2000 National Partnership for ReinventingGovernment Survey of federal employees. The performance variablesincluded managerial effectiveness, customer service orientation,productivity, and work quality. Regression analyses with numerouscontrol variables found that directive, evaluative, and prioritygoal ambiguity related negatively to managerial effectiveness.All four performance indicators showed significant negativerelationships with evaluative goal ambiguity and directive goalambiguity. The results provide further evidence of the viabilityof the new measures of goal ambiguity, support theory-basedbut previously untested hypotheses, and further indicate thefeasibility and value of analyzing goal ambiguity of governmentorganizations.     

Adult Drug Treatment Courts: A Review

Drug treatment courts (DTCs), an alternative to traditional criminal courts, provide an innovative way to legally process some drug offenders. The origin and recent growth of the drug court system in the USA can be explained as an unintended consequence of a failing 'war on drugs'. In this article, we discuss the spread of adult DTCs throughout the USA, the main components of drug courts, controversies surrounding DTCs, and some criticisms of drug courts. We summarize the recent evaluations of adult DTCs, and highlight various DTC factors that have been found to reduce individual drug use and criminal activity. We also offer suggestions for future research on DTCs and conclude with policy recommendations.