A Comparison of Four Imputation Procedures in A Two - Variable Prediction System  

Oleh:

Forsyth, Robert ; Hegamin-Younger, Cecilia

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 58 no. 2 (1998), page 197-210.
Topik: Prediction; imputation procedures; prediction system
Fulltext: 197.pdf (1.2MB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: EE30.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This study compared the effectiveness of four imputation procedures (mean, conditional mean, hot deck and regression) in a two - variable prediction system. A total of 18,869 participants were included in the sample. Two data matrices containing missing values were created : one with randomly missing data and the other with non randomly missing data. Values were missing for only one of the two independent variables. The results of the study provide some support for the following conclusions : a. the grand mean procedure is not an appropriate procedure for handling missing data b. when estimating the regression coefficient of the variable with missing data, the conditional mean procedure should be used, and c. when the prediction of the dependent variable is of interest, the regression procedure should be used.

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