On Calculations Involving the Maximum Cell Frequency

We describe a method of computing the cumulative distribution function of the maximum and minimum cell frequencies in sampling distributions commonly encountered in the analysis of categorical data.The procedure is efficient for exact or approximate calculation in both homogeneous and non-homogeneous cases, is non-recursive, and does not require Dirichlet integrals.Some related statistical problems are also discussed.     

A note on modelling underreported Poisson counts

In this paper we present a parsimonious model for the analysis of underreported Poisson count data. In contrast to previously developed methods, we are able to derive analytic expressions for the key marginal posterior distributions that are of interest. The usefulness of this model is explored via a re-examination of previously analysed data covering the purchasing of port wine (Ramos, 1999).     

Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Psychometric growth curve modeling techniques are used to describe a person’s latent ability and how that ability changes over time based on a specific measurement instrument. However, the same instrument cannot always be used over a period of time to measure that latent ability. This is often the case when measuring traits longitudinally in children. Reasons may be that over time some measurement tools that were difficult for young children become too easy as they age resulting in floor effects or ceiling effects or both. We propose a Bayesian hierarchical model for such a scenario. Within the Bayesian model we combine information from multiple instruments used at different age ranges and having different scoring schemes to examine growth in latent ability over time. The model includes between-subject variance and within-subject variance and does not require linking item specific difficulty between the measurement tools. The model’s utility is demonstrated on a study of language ability in children from ages one to ten who are hard of hearing where measurement tool specific growth and subject-specific growth are shown in addition to a group level latent growth curve comparing the hard of hearing children to children with normal hearing.KEYWORDS: Bayesian hierarchical models, psychometric modeling, language ability, growth curve modeling, longitudinal analysis     

Service diversification and growth of professional service firms

This study investigates the impact of service diversification on the rate and mode of firm growth in professional service firms (PSFs). Drawing on the extant PSF literature, we identify differing views regarding the growth impact of service diversification. Specifically, some scholars suggest that the external client benefits associated with service diversification should allow PSFs to expand revenues at a rapid pace and pursue less merger and acquisition activity, whereas others imply that increased diversification can cause internal challenges with respect to learning costs, coordination and innovation that can limit the rate of revenue growth and encourage more mergers and acquisitions. We test these competing views using longitudinal data on 137 accounting firms and cross-sectional data on 125 law firms and find that service diversification is negatively associated with the rate of firm revenue growth and positively associated with the use of mergers and acquisitions.     

Harm reduction for cannabis: Factor analysis of a protective behavioral strategies survey

Objective: To examine the psychometric properties of a measure of cannabis-specific Protective Behavioral Strategies (PBS), which assesses ways in which students may reduce cannabis-related risk. Participants: Respondents to the American College Health Association – National College Health Assessment II (N = 580) during Spring 2015. Methods: Exploratory Factor Analysis (EFA) and Exploratory Structural Equation Modeling (ESEM) were used to identify and replicate the factor structure of the measure. Results: Results support a four-factor model (Respiratory Health, Frequency/Quantity, Socializing, and General Health) with close approximate fit (Χ² (310) = 565.96, p < .001, RMSEA = .038 (.033, .043; 90% CI), CFI = .961, TLI = .929, SRMR = .033). Support for the convergent validity and construct validity of the measure was also found. Conclusions: This is the initial step in the development of a standard, psychometrically validated measure of cannabis PBS that has the potential to inform future research and interventions.     

VARIANCE FUNCTION REGRESSIONS FOR STUDYING INEQUALITY

Regression-based studies of inequality model only between-group differences, yet often these differences are far exceeded by residual inequality. Residual inequality is usually attributed to measurement error or the influence of unobserved characteristics. We present a model, called  variance function regression , that includes covariates for both the mean and variance of a dependent variable. In this model, the residual variance is treated as a target for analysis. In analyses of inequality, the residual variance might be interpreted as measuring risk or insecurity. Variance function regressions are illustrated in an analysis of panel data on earnings among released prisoners in the National Longitudinal Survey of Youth. We extend the model to a decomposition analysis, relating the change in inequality to compositional changes in the population and changes in coefficients for the mean and variance. The decomposition is applied to the trend in U.S. earnings inequality among male workers, 1970 to 2005.     

College students coping with interpersonal stress: Examining a control-based model of coping

Objective: The ways that college students cope with stress, particularly interpersonal stress, may be a critical factor in determining which students are at risk for impairing mental health disorders. Using a control-based model of coping, the present study examined associations between interpersonal stress, coping strategies, and symptoms. Participants: A total of 135 undergraduate students from 2 universities. Methods: Interpersonal stress, coping strategies, depression, anxiety, and somatization were assessed via self-report. Results: Students reporting more interpersonal stress reported more depression, anxiety, and somatization, and they reported less use of engagement coping strategies and greater use of disengagement coping strategies. Engagement coping strategies accounted for a significant portion of the association between interpersonal stress and mental health symptoms. Unexpectedly, coping strategies did not moderate the association between stress and mental health symptoms. Conclusion: Interventions designed to improve students' coping strategies may be an effective way to reduce mental health problems on college campuses.     

Special education disproportionality in the United States,Germany, Kenya,and India

Disproportionality in special education includes the underrepresentation and overrepresentation of children by gender, economic status, race, ethnicity, language, and culture. This article reviews literature on disproportionality in the United States, Germany, Kenya, and India. Societal views of disability, classism, racism, and inequitable assessment are among the factors that contribute to disproportionality. Preventative medicine, equitable access to resources, ethical and effective assessment procedures, and educational practices that are gender equitable and culturally responsive may reduce the problem of disproportionality.     

Correlates of perceived effectiveness of the Safe Schools/Healthy Students Initiative

A three-level growth-curve model was applied to estimate perceived impact growth trajectories, using multi-year data from project and school surveys on outcome and program implementation collected from 59 sites and approximately 1165 participating schools in the Safe Schools and Healthy Students Initiative. Primary interest is to determine whether and how project-level and school-level correlates affect schools’ perceptions of the Initiative's effectiveness over time when the effects of the pre-grant environmental conditions, grant operations, and near-term outcomes are considered. Coordination and service integration, comprehensive programs and activities for early childhood development, and change in school involvement were found to be significant predictors of school-perceived overall impact when the effect of poverty was considered. Partnership functioning, perceived importance of school resources, and school involvement were found to be significant predictors of school-perceived impact on substance use prevention when the effect of poverty was considered.