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Two-part statistics with paired data.

C Bascoul-Mollevi1, S Gourgou-Bourgade, A Kramar

  • 1CRLC Val d'Aurelle, Biostatistics Unit, Montpellier, France. cmollevi@valdorel.fnclcc.fr

Statistics in Medicine
|November 27, 2004
PubMed
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New statistical tests were developed for paired epidemiological data with many zeros. These methods are more effective than existing ones in most situations, especially for analyzing lower limb venous insufficiency.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Epidemiological studies frequently involve mixed distributions, characterized by zero-inflated data and positive continuous values.
  • Existing statistical methods, like Lachenbruch's tests, address such data in independent samples but require adaptation for paired data.

Purpose of the Study:

  • To adapt Lachenbruch's statistical tests for analyzing paired epidemiological data with zero-inflated distributions.
  • To evaluate the performance of these adapted tests under various conditions of zero proportions and continuous data means.

Main Methods:

  • Developed two new statistics for paired samples, each tending towards a two-degree-of-freedom chi2 distribution.
  • These statistics combine McNemar's test (for zero proportions) with either the Wilcoxon signed-rank test or paired Student's t-test (for positive continuous values).

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Main Results:

  • The adapted two-part statistics demonstrated efficiency when the lower proportion of zeros was associated with the larger mean of the continuous distribution.
  • In other scenarios, the proposed two-part statistics consistently outperformed existing methods.

Conclusions:

  • The developed statistical methods effectively analyze paired epidemiological data with mixed distributions.
  • These tests offer superior performance in most scenarios compared to traditional approaches, particularly in matched case-control studies like the one on lower limb venous insufficiency.