An economic model for clinical quality control

With increased focus on reducing costs in the healthcare industry, the economic aspects of quality control for clinical laboratories must be addressed. In order to evaluate the economic performance of statistical quality control approaches used in the clinical setting, an economic model is developed. Although the economic model is applied specifically to the clinical laboratory in this research, it is easily generalized for use in a wide variety of industry applications. Use of the economic model is illustrated through the comparison of traditional approaches to clinical quality control. Recommendations concerning the performance of the traditional approaches to clinical quality control are provided.     

Exploring Causes of Smart Growth Policy Adoption: Many Challenges Persist*

This article briefly presents the historical evolution of land‐use policies from their origins in the early 20th century to their current form, describes pertinent approaches used in policy adoption and efficacy research, and discusses some of the pitfalls encountered by researchers in this area.     

Discrete-Time Multilevel Hazard Analysis

Combining innovations in hazard modeling with those in multilevel modeling, we develop a method to estimate discrete-time multilevel hazard models. We derive the likelihood of and formulate assumptions for a discrete-time multilevel hazard model with time-varying covariates at two levels. We pay special attention to assumptions justifying the estimation method. Next, we demonstrate file construction and estimation of the models using two common software packages, HLM and MLN. We also illustrate the use of both packages by estimating a model of the hazard of contraceptive use in rural Nepal using time-varying covariates at both individual and neighborhood levels.     

A New Specification Test for the Validity of Instrumental Variables

We develop a new specification test for IV estimators adopting a particular second order approximation of Bekker. The new specification test compares the difference of the forward (conventional) 2SLS estimator of the coefficient of the right‐hand side endogenous variable with the reverse 2SLS estimator of the same unknown parameter when the normalization is changed. Under the null hypothesis that conventional first order asymptotics provide a reliable guide to inference, the two estimates should be very similar. Our test sees whether the resulting difference in the two estimates satisfies the results of second order asymptotic theory. Essentially the same idea is applied to develop another new specification test using second‐order unbiased estimators of the type first proposed by Nagar. If the forward and reverse Nagar‐type estimators are not significantly different we recommend estimation by LIML, which we demonstrate is the optimal linear combination of the Nagar‐type estimators (to second order). We also demonstrate the high degree of similarity for k‐class estimators between the approach of Bekker and the Edgeworth expansion approach of Rothenberg. An empirical example and Monte Carlo evidence demonstrate the operation of the new specification test.     

The Conference Paper-Reviewer Assignment Problem*

Conference organizers often face the following problem: Given a collection of submitted papers, select a subset to be presented at the conference. The bulk of the work often amounts to assembling a pool of reviewers and then sending each submitted paper to several reviewers. We present in this paper a technique for finding a good assignment of papers to reviewers. An important feature of the solution we find is that each paper is sent to at least one reviewer who is “as expert as possible” for that paper. A major component of the problem is modeled as a bottleneck version of a capacitated transshipment problem.     

Attitudes Toward Mental Health Services and Illness Perceptions Among Adolescents with Mood Disorders

The present study describes how adolescents perceive their mood disorders (MD; e.g., acute vs. chronic) and their attitudes toward mental health services. The study also explores the relationships between demographics, clinical characteristics, perceptions of illness and attitudes. Finally, we examine the psychometric properties of the Illness Perception Questionnaire-Revised (Moss-Morris et al. in Psychology & Health 17(1):1–16, 2002). Seventy adolescents were recruited from the greater Cleveland area. Structured interviews were conducted utilizing standardized instruments. Results show that adolescents with MD have fairly positive attitudes, with Caucasian youth reporting more positive attitudes than their non-white ounterparts. Illness perceptions were related to psychological openness and indifference to stigma. Implications are discussed.     

Drawing the Line: An Exploratory Study of Single College Student Perceptions of Marital Boundaries in Opposite Sex Relationships

Marital boundary expectations among single young adults are examined within the context of gender and religiosity among a diverse single young adult sample (n = 422) consisting of college students residing in California, Utah, and Nebraska. Participants (ages 18–29, M = 22.42) completed an online survey and were given extra credit for their participation. The results show that these young adults tend to perceive the need for communication and gift-giving boundaries within the context of heterosexual marriages. Analyses also indicate a trend for women to have higher perceptions of marital boundaries than men and for religiosity (assessed in two different ways) to be linked with marital boundaries. Limitations and recommendations are discussed.     

Inflation of Type I error rate in multiple regression when independent variables are measured with error

When independent variables are measured with error, ordinary least squares regression can yield parameter estimates that are biased and inconsistent. This article documents an inflation of Type I error rate that can also occur. In addition to analytic results, a large‐scale Monte Carlo study shows unacceptably high Type I error rates under circumstances that could easily be encountered in practice. A set of smaller‐scale simulations indicate that the problem applies to various types of regression and various types of measurement error. The Canadian Journal of Statistics 37: 33‐46; 2009 © 2009 Statistical Society of Canada     

L1 ESTIMATION IN SMALL SAMPLES WITH LAPLACE ERROR DISTRIBUTIONS

In this paper a Monte Carlo sampling study consisting of four experiments is described. Two error distributions were employed, the normal and the Laplace; and two small sample sizes (20 and 40) were tested. The question of simultaneous-equation bias called for two-stage estimators. The L¹, norm was employed as a means of comparing the performance of the L¹ or least squares estimators. A relatively new algorithm for computing the direct least absolute (DLA) and two-stage least absolute (TSLA) estimators was employed for the experiments. The results confirmed the hypotheses that for non-normal error distributions such as the Laplace the least absolute estimators were better.