Descripción
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Background: All meta-analyses should include a heterogeneity analysis. Even so, it is not easy to decide whether a set of studies are homogeneous or heterogeneous because of the low statistical power of the statistics used (usually the Q test). Objective: Determine a set of rules enabling SE researchers to find out, based on the characteristics of the experiments to be aggregated, whether or not it is feasible to accurately detect heterogeneity. Method: Evaluate the statistical power of heterogeneity detection methods using a Monte Carlo simulation process. Results: The Q test is not powerful when the meta-analysis contains up to a total of about 200 experimental subjects and the effect size difference is less than 1. Conclusions: The Q test cannot be used as a decision-making criterion for meta-analysis in small sample settings like SE. Random effects models should be used instead of fixed effects models. Caution should be exercised when applying Q test-mediated decomposition into subgroups. | |
Internacional
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No |
Nombre congreso
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ESEM - International Symposium on Empirical Software Engineering and Measurement |
Tipo de participación
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960 |
Lugar del congreso
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Banff, Alberta (CANADA) |
Revisores
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Si |
ISBN o ISSN
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978-1-4577-2203-5 |
DOI
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Fecha inicio congreso
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19/09/2011 |
Fecha fin congreso
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23/09/2011 |
Desde la página
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68 |
Hasta la página
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76 |
Título de las actas
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ESEM 2011 Fifth International Symposium on Empirical Software Engineering and Measurement |