Order selection tests with multiply imputed data
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References listed on IDEAS
- Horton, Nicholas J. & Kleinman, Ken P., 2007. "Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models," The American Statistician, American Statistical Association, vol. 61, pages 79-90, February.
- Jerome P. Reiter, 2007. "Small-sample degrees of freedom for multi-component significance tests with multiple imputation for missing data," Biometrika, Biometrika Trust, vol. 94(2), pages 502-508.
- Xiaowei Yang & Thomas R. Belin & W. John Boscardin, 2005. "Imputation and Variable Selection in Linear Regression Models with Missing Covariates," Biometrics, The International Biometric Society, vol. 61(2), pages 498-506, June.
- Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.
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- Lee, Min Cherng & Mitra, Robin, 2016. "Multiply imputing missing values in data sets with mixed measurement scales using a sequence of generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 24-38.
More about this item
KeywordsAkaike information criterion Hypothesis test Multiple imputation Lack-of-fit test Missing data Omnibus test Order selection;
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