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A COMPARISON OF SINGLE SAMPLE AND CROSS‐VALIDATION METHODS FOR ESTIMATING THE MEAN SQUARED ERROR OF PREDICTION IN MULTIPLE LINEAR REGRESSION
Author(s) -
Browne M. W.
Publication year - 1975
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1975.tb00553.x
Subject(s) - mean squared error , mathematics , statistics , mean squared prediction error , linear regression , sample (material) , sample size determination , regression , calibration , mean absolute error , estimation , chemistry , management , chromatography , economics
Two procedures for estimating the mean squared error of prediction of an empirically determined linear prediction equation are examined. The method usually employed makes use of a second validation sample; another method makes use of the calibration sample alone. The mean squared error of estimation is derived for each of the two estimation procedures and a comparison made. A test is provided also for the hypothesis that use of a prespecified subset of predictors results in no increase in the expected mean squared error of prediction.