Journal ArticleDOI
I. Problems and Designs of Cross-Validation 1
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In this paper, the crossvalidation term is used to describe any one of several distinct, though closely related, experimental designs, and it may be well to identify each of these, to point out their similarities and differences and to make clear the objectives which it serves.Abstract:
THE term &dquo;cross-validation&dquo; is often loosely applied to any one of several distinct, though closely related, experimental designs. Before we get lost in a swamp of semantic confusion, it may be well to identify each of these, to point out their similarities and differences and to make clear the objectives which it serves. What name we give to each is secondary, although for convenience I shall attach a different name to each.read more
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Journal ArticleDOI
On the evaluation of structural equation models
Richard P. Bagozzi,Youjae Yi +1 more
TL;DR: In this article, structural equation models with latent variables are defined, critiqued, and illustrated, and an overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence.
Journal ArticleDOI
Construct validity in psychological tests.
Lee J. Cronbach,Paul E. Meehl +1 more
TL;DR: The present interpretation of construct validity is not "official" and deals with some areas where the Committee would probably not be unanimous, but the present writers are solely responsible for this attempt to explain the concept and elaborate its implications.
Journal ArticleDOI
Cross-Validatory Choice and Assessment of Statistical Predictions
TL;DR: In this article, a generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription, and examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.
Journal ArticleDOI
Single Sample Cross-Validation Indices for Covariance Structures.
Michael W. Browne,Robert Cudeck +1 more
TL;DR: This article considers single sample approximations for the cross-validation coefficient in the analysis of covariance structures and suggests an adjustment for predictive validity which may be employed in conjunction with any correctly specified discrepancy function.
Journal Article
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory
TL;DR: In this article, the authors theoretically compare the Bayes cross-validation loss and the widely applicable information criterion and prove two theorems: 1) The Bayes generalization error is asymptotically equal to 2λ/n, where λ is the real log canonical threshold and n is the number of training samples.