The South Carolina LGBT Needs Assessment: A Descriptive Overview

Limited quantitative information exists about the demographics and needs of lesbian, gay, bisexual, and transgender (LGBT) persons in South Carolina, a predominately rural Southern state. Responses to a needs assessment survey (n = 715) were analyzed to understand the diversity and needs of members of the LGBT community in SC. The purpose was to inform future programming and guide the development of a more comprehensive portfolio of services to be offered by a local LGBT community center. Findings suggest that a diverse LGBT community exists in SC and needs include increased programming for community members as well as efforts to provide policy-level support and increased acceptability and understanding of LGBT persons in South Carolina.     

Bayesian assessment of assumptions of regression analysis

Many statistical procedures are based on the models which specify the conditions under which the data are generated. Many applications of linear regression, for example, assume that:(i) the observations are independent; (ii) the errors in the observations are identically distributed; (iii) each error has a normal distribution with mean zero and unknown variance σ²> 0. Previous works have examined individual departures from these assumptions. Here we examine composite departures. It is assumed that the error distribution in a linear model is power-exponential and that the observations are generated via a first order autoregressive model with the possibility of spurious observations. The consequences are illustrated via an example.     

The Role of the Statistician: Scientist or Shoe Clerk

A carnival game is described in which a player rolls eight dice or eight marbles into holes. To win, the player must obtain a favorable outcome on a number of plays. The probability distribution for the outcome of a single play is discussed. The distribution of a winning combination of outcomes is discussed and approximated. These probabilities show that the game is essentially unbeatable.     

Use of weighted least squares regression jn simulation studies

When a simulation or Monte Carlo analysis uses the same set of N samples as input for the comparison of the power of tests, the resulting estimates of power are highly correlated. As a result, the statistical analysis of these results should use weighted least squares or other equivalent procedures. A reanalysis of one simulation study (Thode et al., 1983) found that the weighted least squares estimates had much smaller standard errors than the ordinary least squares estimates. The reduction in the standard errors of the parameters was a factor between 4 and 9 for the tests found to be more powerful. The necessary calculations are described.     

Bayesian analysis of reliability in multicomponent stress-strength models

This paper provides a Bayesian treatment of the problem of inference about the reliability of a multicomponent stress-strength system which functions if s or more of k identical components simultaneously operate. All stresses and strengths are assumed to be independent, exponentially distributed random variables. Exact and approximate asymptotic posterior distributions for the reliability are derived, and the results are illustrated by a numerical example.     

Bayesian Inference in Multivariate Regression With Missing Observations on the Response Variables

We discuss the case of the multivariate linear model Y = XB + E with Y an (n × p) matrix, and so on, when there are missing observations in the Y matrix in a so-called nested pattern. We propose an analysis that arises by incorporating the predictive density of the missing observations in determining the posterior distribution of B, and its mean and variance matrix. This involves us with matric-T variables. The resulting analysis is illustrated with some Canadian economic data.     

Beyond Absenteeism: Father Incarceration and Child Development

High rates of incarceration among American men, coupled with high rates of fatherhood among men in prison, have motivated recent research on the effects of parental imprisonment on children’s development. We use data from the Fragile Families and Child Wellbeing Study to examine the relationship between paternal incarceration and developmental outcomes for approximately 3,000 urban children. We estimate cross-sectional and longitudinal regression models that control not only for fathers’ basic demographic characteristics and a rich set of potential confounders, but also for several measures of pre-incarceration child development and family fixed effects. We find significant increases in aggressive behaviors and some evidence of increased attention problems among children whose fathers are incarcerated. The estimated effects of paternal incarceration are stronger than those of other forms of father absence, suggesting that children with incarcerated fathers may require specialized support from caretakers, teachers, and social service providers. The estimated effects are stronger for children who lived with their fathers prior to incarceration but are also significant for children of nonresident fathers, suggesting that incarceration places children at risk through family hardships including and beyond parent-child separation.     

Shortest confidence and prediction intervals for the log-normal

We provide the shortest prediction interval for X, and the shortest confidence interval for the median of X, when X has the log-normal distribution for both the case σ², the variance of log X, known and unknown. Tables are given to assist the practitioner in constructing these intervals. A real-life example is provided to illustrate the results.     

Quality of life assessment and drug abuse treatment program evaluation

Quality of life assessment is used as an outcome measure technique to evaluate a central medical intake (CMI) unit for drug treatment programs. While significant improvements across time are evident in both perceived well-being and in the standard federal funding criteria, no differences are observed between those referred into treatment by the CMI and those entering directly. Moreover, the improvements observed are the same regardless of whether the patient stayed in treatment or not.