Showing papers by "Allan Donner published in 2004"

Pitfalls of and controversies in cluster randomization trials.

Abstract: It is now well known that standard statistical procedures become invalidated when applied to cluster randomized trials in which the unit of inference is the individual. A resulting consequence is that researchers conducting such trials are faced with a multitude of design choices, including selection of the primary unit of inference, the degree to which clusters should be matched or stratified by prognostic factors at baseline, and decisions related to cluster subsampling. Moreover, application of ethical principles developed for individually randomized trials may also require modification. We discuss several topics related to these issues, with emphasis on the choices that must be made in the planning stages of a trial and on some potential pitfalls to be avoided.

Sample size requirements for the design of reliability study: review and new results

Abstract: The reliability of continuous or binary outcome measures is usually assessed by estimation of the intraclass correlation coefficient (ICC). A crucial step for this purpose is the determination of the required sample size. In this review, we discuss the contributions made in this regard and derive the optimal allocation for the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for both normally and non-normally distributed responses, with emphasis on the case of dichotomous assessments. Tables showing optimal choices of k and n are given along with the guidelines for the efficient design of reliability studies.

Confidence interval estimation of the intraclass correlation coefficient for binary outcome data.

Abstract: We obtain closed-form asymptotic variance formulae for three point estimators of the intraclass correlation coefficient that may be applied to binary outcome data arising in clusters of variable size. Our results include as special cases those that have previously appeared in the literature (Fleiss and Cuzick, 1979, Applied Psychological Measurement 3, 537-542; Bloch and Kraemer, 1989, Biometrics 45, 269-287; Altaye, Donner, and Klar, 2001, Biometrics 57, 584-588). Simulation results indicate that confidence intervals based on the estimator proposed by Fleiss and Cuzick provide coverage levels close to nominal over a wide range of parameter combinations. Two examples are presented.

Methods for the Statistical Analysis of Binary Data in Split‐Cluster Designs

Abstract: Split-cluster designs are frequently used in the health sciences when naturally occurring clusters such as multiple sites or organs in the same subject are assigned to different treatments. However, statistical methods for the analysis of binary data arising from such designs are not well developed. The purpose of this article is to propose and evaluate a new procedure for testing the equality of event rates in a design dividing each of k clusters into two segments having multiple sites (e.g., teeth, lesions). The test statistic proposed is a generalization of a previously published procedure based on adjusting the standard Pearson chi-square statistic, but can also be derived as a score test using the approach of generalized estimating equations.

Flexible client-driven in-home case management: an option to consider.

Abstract: Changes in health services and care needs have created high demand for case management of in-home services. To address this challenge, several models of case management have been used. Evaluations to date suggest that clients need different approaches for different circumstances at different times to optimize cost-effectiveness. Accordingly, one Canadian home care program adopted flexible client-driven case management engaging clients as partners in flexibly selecting either an integrated team, consumer-managed or brokerage model of case management in keeping with their preferences and abilities. Using an exploratory, multimeasure quasi-experimental design, a generic model of program evaluation, and both quantitative and qualitative methods, researchers identified challenges in implementing this intervention, policy impediments the clients characteristically in each of the three case management models, and client, provider, and caregiver outcomes of flexible, client-driven care. While further longitudinal investigation is needed findings suggest several important considerations for those interested in this option for care management. Alternative case management models do attract different client groups, and having a choice does not alter care costs or outcomes. Flexible client-driven case management may be experienced positively by case managers and other providers.