Psychology Commons^™

A Positive Trait Item Response Model, Joseph F. Lucke

Joseph Lucke

All current models from item response theory (IRT) assume the latent trait follows a standard normal distribution. While this assumption is appropriate for traits such as ability or attitude, it creates both conceptual and technical problems traits such as addiction (alcohol, drugs, gambling). The distribution of an addiction trait is better assumed to be anchored at zero (no addiction) and positively skewed. A small change to the usual IRT model yields a class of positive-trait item response models (PTIRMs). I discuss PTIRMs and present one model in detail, including item characteristic curves and item information curves. I present an example …

Positive Trait Item Response Models, Joseph F. Lucke

Joseph Lucke

A new item response model is proposed for which the trait is positive. Three such models, the loglogistic, the log-normal, and the Weibull, are presented along with their item information curves. The data of seven addiction items from the DSM-IV from a study on alcohol addiction is analyzed by these three models using Bayesian Markov chain Monte Carlo methods. The item characteristic curves and item information curves are presented for all three models. The person scores for four item response patterns are presented for the log-logistic model.

A Critique Of The False-Positive Report Probability, Joseph Lucke

Joseph Lucke

The false positive report probability (FPRP) was proposed as a Bayesian prophylactic against false reports of significant associations. Unfortunately, the derivation of the FPRP is unsound. A heuristic derivation fails to make its point, and a formal derivation reveals a probabilistic misrepresentation of an observation. As a result, the FPRP can yield serious inferential errors. In particular, the FPRP can use an observation that is many times more likely under the null hypothesis than under the alternative to infer that the null hypothesis is far less probable than the alternative. Contrary to its intended purpose, the FPRP can promote false …

Evaluation Of Heterogeneity In Pharmacotherapy Trials For Drug Dependence: A Bayesian Approach, Charles E. Green, F. G. Moeller, J. M. Schmitz, Joseph F. Lucke, S. D. Lane, A. C. Swann, Robert E. Lasky, Joseph P. Carbonari

Joseph Lucke

Difficulty identifying effective pharmacotherapies for cocaine dependence has led to suggestions that subgroup differences may account for some of the heterogeneity in treatment response. Well-attested methodologicalifficulties associated with these analyses recommend the use of Bayesian statistical reasoning for evaluation of salient interaction effects.

Methods: A secondary data analysis of a previously published, double-blind, randomized controlled trial examines the interaction of decision-making, as measured by the Iowa Gambling Task, and citalopram in increasing longest sustained abstinence from cocaine use.

Results: Bayesian analysis indicated that there was a 99% chance that improved decision-making enhances response to citalopram. Given the strong positive nature …

Bayesian Statistics, Joseph F. Lucke

Joseph Lucke

No abstract provided.

Effects Of Support On The Initiation And Duration Of Breastfeeding, Sara L. Gill, Elizabeth Reifsnider, Joseph F. Lucke

Joseph Lucke

Researchers attempted to increase the initiation of breastfeeding and its duration to 6 months among a group of low-income, Hispanic women through an intervention program which included prenatal education and home based postpartum support. All participants were telephoned after delivery to determine infant feeding method. Duration of breastfeeding was determined by counting the number of days from initiation to the last day the baby was put to the breast. The Bayesian approach was used for the statistical analyses. In the intervention group, the propensity to initiate breastfeeding exceeded that of the control group. Results indicate the intervention group had twice …

Predicting Breast-Feeding Attrition: Adapting The Breast-Feeding Attrition Prediction Tool, Elizabeth Reifsnider, Sarah L. Gill, Joseph F. Lucke, Angela R. Mann

Joseph Lucke

CONTEXT: Current breast-feeding rates fall short of the recommendations set forth in Health People 2010. The Breast-feeding Attrition Prediction Tool (BAPT), administered in the postpartum period, has been useful in predicting breast-feeding attrition. However, assessing a woman's intention to breast-feed prior to birth would identify women at risk for breast-feeding attrition.

PURPOSE: The purpose of this study was to describe a revised BAPT, administered antepartally that measures intention to breast-feed.

METHODS: The BAPT, comprising 94 items on a 6-point Likert-type scale, was translated into Spanish and back-translated for accuracy. The BAPT was then revised by reducing the number of items …

Fall Prevention Programs For The Elderly: A Bayesian Secondary Meta-Analysis, Joseph F. Lucke

Joseph Lucke

A secondary meta-analysis of programs to reduce falls in the elderly is undertaken to demonstrate a Bayesian analysis. The Bayesian statistical tradition is carefully distinguished from the standard Neyman-Pearson-Wald (NPW) statistical tradition. In the 12 studies, the logit effect size is used to compare treatment groups using a prevention program to control groups without a program. To contrast the Bayesian analysis, independent-effects and fixed-effect meta-analyses are first conducted in the NPW tradition. This is followed by Bayesian independent-effects and fixed-effect meta-analyses that numerically replicate the NPW results but have conceptually different interpretations. The final analyses comprise Bayesian random-effects and predictive …

Benchmarking Patient Outcomes, Ellen B. Rudy, Joseph F. Lucke, Gayle R. Whitman, Lynda J. Davidson

Joseph Lucke

Purpose: To examine the usefulness of three types of benchmarking for interpreting patient outcome data.

Design: This study was part of a multiyear, multihospital longitudinal survey of 10 patient outcomes. The patient outcome used for this methodologic presentation was central line infections (CLI). The sample included eight hospitals in an integrated healthcare system, with a range in size from 144 to 861 beds. The unit of analysis for CLI was the number of line days, with the CLI rate defined as the number of infections per 1,000 patient-line days per month.

Methods: Data on each outcome were collected at the …