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.     

Proportional reversed hazard rate model and its applications

The purpose of this paper is to study the structure and properties of the proportional reversed hazard rate model (PRHRM) in contrast to the celebrated proportional hazard model (PHM). The monotonicity of the hazard rate and the reversed hazard rate of the model is investigated. Some criteria of aging are presented and the inheritance of the aging notions (of the base distribution) by the PRHRM is studied. Characterizations of the model involving Fisher information are presented and the statistical inference of the parameters is discussed. Finally, it is shown that several members of the proportional reversed hazard rate class have been found to be useful and flexible in real data analysis.     

Estimation of critical points in the mixture inverse Gaussian model

The maximum likelihood estimation for the critical points of the failure rate and the mean residual life function are presented in the case of mixture inverse Gaussian model. Several important data sets are analyzed from this point of view. For each of the data sets, Bootstrapping is used to construct confidence intervals of the critical points.     

Body Structure Perception in Infancy

Structural cues, such as the relative size and arrangement of parts, are key aspects of adults' representation of human bodies, and they are used to derive significant social information such as age, sex, and attractiveness. Prior studies have not clearly addressed young infants' sensitivity to these body characteristics. In the current experiments, 3.5‐month‐olds exhibited a preference between images of intact bodies versus those with parts in wrong locations. Infants also discriminated between intact bodies and those with distorted part proportions. In both cases, infants discriminated when images were presented upright but not when they were inverted. These results indicate that infants are sensitive to the arrangement and size of human body parts at least by 3.5 months of age. Thus, contrary to some prior reports, body representation early in life is developed enough to include structural information.     

Weighted bivariate logarithmic series distributions

In this paper, we are interested in the weighted distributions of a bivariate three parameter logarithmic series distribution studied by Kocherlakota and Kocherlakota (1990). The weighted versions of the model are derived with weight W(x,y) = x^[r] y^[s]. Explicit expressions for the probability mass function and probability generating functions are derived in the case r = s = l. The marginal and conditional distributions are derived in the general case. The maximum likelihood estimation of the parameters, in both two parameter and three parameter cases, is studied. A procedure for computer generation of bivariate data from a discrete distribution is described. This enables us to present two examples, in order to illustrate the methods developed, for finding the maximum likelihood estimates.     

A generalized improvement procedure for variance bounds for minimum variance unbiased estimator in inverse sampling

New bounds are obtained for the variance of the minimum variance unbiased estimator of p i n inverse sampling. A generalized procedure for further improving the bounds is also discussed.     

Statistical morphology

This paper first introduces a parametric model for the generation of stationary random correlated binary sequences. The parameters of the model include the probability that a pixel is a binary one pixel and the length of the structuring element which dilates the initially spatially uncorrelated sequence. The spatial statistics of such eroded, dilated, opened and closed correlated binary sequences are derived in terms of the spatial statistics of the input binary sequence. Understanding of such one-dimensional processing is a precondition for understanding what happens in the more interesting two- dimensional case.     

Estimation of a bivariate distribution function from incomplete observations

Kaplan and Meier (1958) give a maximum likelihood estimator of the distribution function based on a univariate right censored sample-Here we investigate the extension of their results to the case of bivariate right censored samples. Following Efron (1967), we provide "self-consistent" estimators for the bivariate distribution function.