PubMed · 8295843
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L S Aaronson. Milking data or meeting commitments: how many papers from one study?. https://doi.org/10.1097/00006199-199401000-00013
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Two-part models arise when there is a clump of 0 observations in a distribution of continuous non-negative responses. Several methods for comparing two such distributions are available. These include the straightforward application of the z-test (or t-test), the Wilcoxon-Mann-Whitney rank sum test, the Kolmogorov-Smirnov test, and three tests that use a 2 degree of freedom chi(2) test based on the sum of the test for equality of proportions and a conditional chi(2) test for the continuous responses. This conditional test may be the z-test, the rank sum test, or the chi(2) corresponding to the Kolmogorov-Smirnov test. This study compares the size and power of several of these methods. All tests have the appropriate distribution under the null hypothesis if the distribution of the continuous part has finite moments. If it does not, the z-test has no power to detect any alternatives. It is found that the 2 d.f. tests are superior to the others when the larger proportion of 0 values corresponds to the population with the larger mean. If the reverse holds, the difference in the proportion of zeros reinforces the difference in means and some single-part models (the rank sum or Kolmogorov-Smirnov) do best. In those cases, the two-part models are not far behind, although statistically significantly poorer with respect to power. Published in 2001 by John Wiley & Sons, Ltd.
Two-part models assume the data has a probability mass at zero and a continuous response for values greater than 0. We construct tests based on the proportion of zeros and the difference among the positive values of a response giving rise to a two degree of freedom chi(2) test. This note gives the non-centrality parameter and finds the power for the test. The power is compared to the simulation results in a recent paper. We derive sample size calculations. We note that some modifications of this procedure may provide better tests if the non-zero responses are discrete. Published in 2001 by John Wiley & Sons, Ltd.
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