A new alternative to the standard F test for clustered data |
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Authors: | P Lahiri Yan Li |
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Institution: | 1. Joint Program for Survey Methodology, University of Maryland, College Park 20742, USA;2. Biostatistics Branch, National Cancer Institute, NIH 20852, USA;3. Department of Mathematics, University of Texas, Arlington 76019, USA |
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Abstract: | The data collection process and the inherent population structure are the main causes for clustered data. The observations in a given cluster are correlated, and the magnitude of such correlation is often measured by the intra-cluster correlation coefficient. The intra-cluster correlation can lead to an inflated size of the standard F test in a linear model. In this paper, we propose a solution to this problem. Unlike previous adjustments, our method does not require estimation of the intra-class correlation, which is problematic especially when the number of clusters is small. Our simulation results show that the new method outperforms the existing methods. |
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Keywords: | Clustered data Intra-cluster correlation Standard F test Generalized least square test Fuller&ndash Battese transformation |
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