Effects of Medicaid managed care policies on mental health service use among a national probability sample of children in the child welfare system

Children in the child welfare system are dependent upon Medicaid to finance services for their considerable mental health needs. This study examines the effects of Medicaid policies on mental health service use among a national probability sample of children in the child welfare system. Data for this study came from the National Survey of Child and Adolescent Well-Being, the Caring for Children in Child Welfare study, and the Area Resource File. Weighted multivariate logistic regression analyses were conducted to estimate effects of policy variables on children's use of mental health services, controlling for child-level covariates and county-level health resources. Children in counties with behavioral carve-outs under Medicaid managed care had lower odds of inpatient mental health service use. Medicaid managed care enrollment and variations in type of provider reimbursement did not affect use of mental health services. Older age, greater need for mental health services, and higher levels of caregiver education were associated with increased odds of service use. Restrictions on use of inpatient mental healthcare caused by behavioral carve-outs may disproportionately affect children in the child welfare system who have high rates of such use. Careful adoption of carve-outs is necessary to assure appropriate care for these children.     

The current state of the labor queue: National and regional Evidence

We employ vector autoregressive techniques to determine the current state of the labor queue. Unemployment rate differentials have narrowed in recent years, potentially due to a change in the queue ordering, though a tight labor market and a stable queue would yield similar results. We find no evidence that the queue ordering has changed, which brings into question the resiliency of gains made by minority groups. We employ the same techniques to reveal the state of the queue across geographic regions and find that substantial differences exist across regions, implying variation in the relative labor force status of demographic groups.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

Banks winners in tournaments are difficult to recognize

Given a tournament T, a Banks winner of T is the top vertex of any maximal (with respect to inclusion) transitive subtournament of T. In this technical note, we show that the problem of deciding whether some fixed vertex v is a Banks winner for T is NP-complete. Received: 22 February 2002/Accepted: 20 June 2002 Supported by the START program Y43-MAT of the Austrian Ministry of Science. I would like to thank two thank the referees for a careful reading of the paper, for helpful remarks, and for many suggestions how to improve the presentation.