A Method for Comparing Positive Rates of Two Blood Culture Systems

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Abstract
McNemar's test is used to compare two marginal positive rates from an independent sample of paired binary data. When the pairs are not mutually independent, the McNemar's test may not be valid. In this paper, we propose a random-effects regression model for comparing two marginal probabilities from nonindependent matched pairs data with covariates. An example of comparing positive rates of two blood culture systems illustrates this method. In this example, there is no external gold standard, the paired data are clustered, the data with negative results from both systems are not available, and one culture-specific covariate is involved. The computing method for the maximum likelihood estimation is efficient.

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