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Biomedical subjects

Guangyong Zou

Publications and source records attributed to Guangyong Zou.

8 recordsLinked to original sources
PubMed2005

A non-iterative confidence interval estimating procedure for the intraclass kappa statistic with multinomial outcomes.

We obtain the asymptotic sample variance of the intraclass kappa statistic for multinomial outcome data. A modified Wald type procedure based on this theory is then used for confidence interval construction. The results of a simulation study show that the proposed non-iterative approach performs very well in terms of confidence interval coverage and width for samples as small as 50. The procedure is illustrated with two examples from previously published medical studies.

Carotid Stenosis↗
PubMed2004

A modified poisson regression approach to prospective studies with binary data.

Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.

Clinical Trials as Topic↗
PubMed2004

A simple alternative confidence interval for the difference between two proportions.

The difference between two proportions is often the focus of interest in prospective comparative studies such as randomized controlled trials that have a binary outcome. Consequently, interval estimation for this parameter has received considerable attention in the literature. A hybrid procedure resulting from combining two sets of confidence limits for a single proportion as proposed by Newcombe has been previously recommended for this purpose because of its superior properties and relative simplicity. In this paper, we propose a simple alternative approach based on Fisher's z transformation. The results of an exact evaluation study show that this new procedure performs as well as Newcombe's procedure in terms of percent coverage and expected confidence interval width. Several examples are presented.

Algorithms↗
PubMed2004

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

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.

Biometry↗
PubMed2004

Methods for the statistical analysis of binary data in split-cluster designs.

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.

Anti-Infective Agents, Local↗
PubMed2002

Interval estimation for a difference between intraclass kappa statistics.

Model-based inference procedures for the kappa statistic have developed rapidly over the last decade. However, no method has yet been developed for constructing a confidence interval about a difference between independent kappa statistics that is valid in samples of small to moderate size. In this article, we propose and evaluate two such methods based on an idea proposed by Newcombe (1998, Statistics in Medicine, 17, 873-890) for constructing a confidence interval for a difference between independent proportions. The methods are shown to provide very satisfactory results in sample sizes as small as 25 subjects per group. Sample size requirements that achieve a prespecified expected width for a confidence interval about a difference of kappa statistic are also presented.

Computer Simulation↗
PubMedDate not supplied

From diagnostic accuracy to accurate diagnosis: interpreting a test result with confidence.

BACKGROUND: The Standard for Reporting of Diagnostic Accuracy statement promotes the reporting of confidence intervals (CIs) for indices of diagnostic test accuracy. However, these indices must be combined with an estimate of pretest probability to properly interpret the results of such tests, thus yielding positive and negative predictive values. For small sample sizes, CI estimation for predictive values based on the classical logit transformation has been found to be very conservative. A method based on computer simulation has therefore been suggested as an alternative. METHODS: ACI procedure for predictive values that yields limits completely contained in those provided by the logit transformation is proposed and evaluated. RESULTS: The proposed approach to CI construction maintains nominal coverage very well even when sample sizes are small. CONCLUSION: Accurate CIs for positive and negative predictive values can be obtained without using computer simulation.

Bayes Theorem↗