Economic Modeling Triggers More Efficient Planning: An Experimental Justification

Consider a firm as an organization that needs to efficiently coordinate several specialized departments in an uncertain environment. Decision making involves collective planning sessions and decentralized operational processes. In this setting this paper explores the role of economic modeling through an experimental game. Results support the idea that economic modeling favors higher performance. Economic modeling facilitates the emergence of common knowledge and the decomposition of a group decision problem into individual decision problems that are meaningfully interrelated. This paper was presented at the Porquerolles Summer School on Cognitive Sciences, September 2001.     

Drug resistance in an age-of-infection model

ABSTRACT

In the case of a disease spreading over a time-scale comparable to the average lifetime in a host population, when the infectiousness of individuals depends on the tine since the onset of infection and when infections involve both drug-sensitive and drug-resistant strains of a pathogen, resistance may develop during the treatment of drug-sensitive strains. If increasing the treatment rate reduces the reproduction number of the drug-sensitive strain to a value below the reproduction number of the drug-resistant strain, then the disease may persist at a boundary equilibrium where only drug-resistant infection is present.     

Effect of aggregation on the estimation of trend in mortality

There are three approaches to analyzing and forecasting age‐specific mortality: (1) analyze age‐specific data directly, (2) analyze each cause‐specific mortality series separately and add the results, (3) analyze cause‐specific mortality series jointly and add the results. We show that if linear models are used for cause‐specific mortality, then the three approaches often give close results even when cause‐specific series are correlated. This result holds for cross‐correlations arising from random misclassification of deaths by cause, and also for certain patterns of systematic misclassification. It need not hold, if one or more causes serve as “leading indicators”; for the remaining causes, or if outside information is incorporated into forecasting either through expert judgment or formal statistical modeling. Under highly nonlinear models or in the presence of modeling error the result may also fail. The results are illustrated with U.S. age‐specific mortality data from 1968–1985. In some cases the aggregate forecasts appear to be the more credible ones.     

Longitudinal links of parental solicitation,knowledge, and peer approval with deviance during early adolescence

The current study examined growth-to-growth associations of parental solicitation, knowledge, and peer approval with deviance during early adolescence, using a 4-wave, 18-month self-reported longitudinal data set from 570 Czech early adolescents (58.4% female; M_age = 12.43 years, SD = 0.66 at baseline). Unconditional growth model tests provided evidence of significant changes in the three parenting behaviors and in deviance over time. Multivariate growth model tests showed that declines in maternal knowledge were associated with increases in deviance, while greater increases in parental peer approval were associated with slower increases in deviance. Findings provide evidence of dynamic changes in parental solicitation, knowledge, and peer approval over time, as well as in deviance; additionally, they importantly show how parental knowledge and peer approval covary developmentally with deviance.     

Associations between hope and trajectories of critical consciousness among U.S. youth of color

We examined associations between hope as an internal asset that supports positive youth development, and growth trajectories of three critical consciousness components. Using five waves of data collected over the course of high school (N = 618), we modeled growth trajectories of awareness of inequity (critical reflection), a sense of agency about taking sociopolitical action (critical agency), and behaviors targeting systems of oppression (critical action). Hope was highest among those with high trajectories of critical agency and critical action. Clear associations with hope emerged at the last time point for critical reflection, suggesting that sustained growth in critical reflection is associated with hope. When supporting the critical consciousness development of youth of color, concurrent support for hope may be instrumental.     

Concept mapping as an approach for expert-guided model building: The example of health literacy

Concept mapping served as the starting point for the aim of capturing the comprehensive structure of the construct of ‘health literacy.’ Ideas about health literacy were generated by 99 experts and resulted in 105 statements that were subsequently organized by 27 experts in an unstructured card sorting. Multidimensional scaling was applied to the sorting data and a two and three-dimensional solution was computed. The three dimensional solution was used in subsequent cluster analysis and resulted in a concept map of nine “clusters”: (1) self-regulation, (2) self-perception, (3) proactive approach to health, (4) basic literacy and numeracy skills, (5) information appraisal, (6) information search, (7) health care system knowledge and acting, (8) communication and cooperation, and (9) beneficial personality traits. Subsequently, this concept map served as a starting point for developing a “qualitative” structural model of health literacy and a questionnaire for the measurement of health literacy. On the basis of questionnaire data, a “quantitative” structural model was created by first applying exploratory factor analyses (EFA) and then cross-validating the model with confirmatory factor analyses (CFA). Concept mapping proved to be a highly valuable tool for the process of model building up to translational research in the “real world”.     

Assessing program impact using latent growth modeling: a primer for the evaluator

Latent growth modeling (LGM) has emerged as a flexible analytic technique for modeling change over time because it can describe developmental processes at both the inter- and intra-individual levels. The LGM method can also provide a means for testing the contribution of other variables in order to explain variability in growth trajectories. This paper didactically illustrates the use of LGM as an analytical tool in program evaluation. Specifically, a hypothetical evaluation of a high school drug prevention program was used to demonstrate: (a) how LGM can be used to assess the longitudinal impact of a prevention program by comparing treatment and control populations with respect to individual differences in initial status and in rate of change; and (b) how predictors of initial status (post-intervention) and growth selected on the basis of a particular program theory can be incorporated in the model to explain program impact. Some advantages and limitations of using LGM in program evaluation are highlighted.     

Max‐infinitely divisible models and inference for spatial extremes

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max‐stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max‐infinitely divisible processes, which extend max‐stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max‐infinitely divisible models, which relax the max‐stability property but remain close to some popular max‐stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max‐stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student‐t copula process and its max‐stable limit, even for large block sizes.     

Social capital in Croatia: measurement and regional distribution

By using partial least squares path modeling, this paper develops a complex index of social capital, selects Croatia as the case for testing and validating the index, and investigates the regional distribution of social capital. The social capital index is defined as a complex hierarchical structured construct of third-order with social trust, participation, and civism as its core dimensions. The main results indicate that civism is the most important cause of social capital followed by active participation and social trust. As far as the regional distribution of social capital is concerned, there are statistically significant differences across the Croatian regions. Although the lowest or below the national average level of social capital and its dimensions can be mostly found in the least developed regions (with the exception of the capital), the highest level of social capital and its particular dimensions is not achieved in the most developed regions.     

Parental Work Schedules and Children's Cognitive Trajectories

Previous work has shown an association between mothers' nonstandard work schedules and children's well-being. We built on this research by examining the relationship between parental shift work and children's reading and math trajectories from age 5/6 to 13/14. Using data (N=7,105) from the National Longitudinal Survey of Youth and growth curve modeling, we found that children's math and reading trajectories were related to parents' type of nonstandard shifts (i.e., evening, night, or variable). We found that having a mother who worked more years at a night shift was associated with lower reading scores, having a mother work more years at evening or night shifts was associated with reduced math trajectories, and having a father work more years at an evening shift was associated with reduced math scores. Mediation tests suggest that eating meals together, parental knowledge about children's whereabouts, and certain after-school activities might help explain these results.