Randomly Missing Data in Multiple Regression [electronic resource] : An Empirical Comparison of Common Missing Data Treatments / Jeffrey D. Kromrey and Constance V. Hines.

An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootst...

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Bibliographic Details

Online Access:	Full Text (via ERIC)
Main Author:	Kromrey, Jeffrey D.
Other Authors:	Hines, Constance V.
Format:	Electronic eBook
Language:	English
Published:	[S.l.] : Distributed by ERIC Clearinghouse, 1991.
Subjects:	Comparative Analysis. Computer Simulation. Estimation (Mathematics) Mathematical Models. Multiple Regression Analysis. Sample Size. Statistical Bias.