Prediction of Missing Data Using Regression Models: A Programmed Approach for Large SPSS System Files
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Keywords

Regression analysis--Mathematical models

Abstract

The purpose of this article is to present computer programming capable of automatically predicting missing data in an SPSS system file using multiple regression-techniques. Two versions are presented. The first is an interactive approach designed to run via VSPC under OS/VS MVS. The second is designed to be used in a card batch environment. In addition, an equation which predicts the amount of CPU time required is included.

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Copyright (c) 1981 Ron Bobner, Hal Stalcup, Isadore Newman, Carolyn Benz (Author)

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