The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Cross validatory choice and assessment of statistical predictions
Abstract
Summary 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. The examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“A long-standing practice in that literature is to use different partitions of the data for model estimation and inference, referred to as sample splitting (Larson, 1931; Stone, 1974).”
From Auditing a Dutch Public Sector Risk Profiling Algorithm Using an Unsupervised Bias Detection Tool (2025) · cites this paper as Stone, 1974
In the citing paper
“The performance of the model on such a setup is estimated to be the mean of the k validation results [19,20,21].”
From Fully Automated Placental Volume Quantification From 3D Ultrasound for Prediction of Small‐for‐Gestational‐Age Infants (2022) · cites this paper as [20]
Citations
Cites
The Handbook of Social Psychology
Gravatt, A. E., Lindzey, G. E., & Aronson, F. (1969) · The Family Coordinator · doi:10.2307/582242 · Cited by 12,518
Rozeboom, W. W., Lord, F. M., Novick, M. R., & Birnbaum, A. (1969) · American Educational Research Journal · doi:10.2307/1162101 · Cited by 8,012
Optimal Statistical Decisions.
Siegmund, D., & DeGroot, M. H. (1972) · Journal of the American Statistical Association · doi:10.2307/2284675 · Cited by 3,436
A Predictive Approach to the Random Effect Model
Geisser, S. (1974) · Biometrika · doi:10.1093/biomet/61.1.101 · Cited by 3,101
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
Estimation of Error Rates in Discriminant Analysis
Lachenbruch, P. A., & Mickey, M. R. (1968) · Technometrics · doi:10.1080/00401706.1968.10490530 · Cited by 1,560
The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction
Allen, D. M. (1974) · Technometrics · doi:10.1080/00401706.1974.10489157 · Cited by 1,469
Inference and disputed authorship : The Federalist
Mosteller, F. C., & Wallace, D. K. (1964) · Medical Entomology and Zoology · Cited by 916
Mean Square Error of Prediction as a Criterion for Selecting Variables
Allen, D. M. (1971) · Technometrics · doi:10.1080/00401706.1971.10488811 · Cited by 687
Robertson, C., Andrews, D. F., Bickel, P. J., Hanpel, F. R., Huber, P. J., Rogers, W. H., & Tukey, J. W. (1972) · Biometrics · doi:10.2307/2528653 · Cited by 462
Randolph, P. H., & Groot, M. D. (1970) · Technometrics · doi:10.2307/1267221 · Cited by 424
Mean Square Error of Prediction as a Criterion for Selecting Variables
Allen, D. M. (1971) · Technometrics · doi:10.2307/1267161 · Cited by 362
I. Problems and Designs of Cross-Validation 1
Mosier, C. I. (1951) · Educational and Psychological Measurement · doi:10.1177/001316445101100101 · Cited by 315
Statistics and experimental design
(1990) · Reproductive Toxicology · doi:10.1016/0890-6238(90)90011-j · Cited by 305
Selection of Variables for Fitting Equations to Data
Gorman, J. W., & Toman, R. J. (1966) · Technometrics · doi:10.1080/00401706.1966.10490322 · Cited by 282
The prediction of personal adjustment.
Stuit, D. B. (1942) · Psychological Bulletin · doi:10.1037/h0052603 · Cited by 275
A New Formula for Predicting the Shrinkage of the Coefficient of Multiple Correlation
Wherry, R. J. (1931) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177732951 · Cited by 274
Confidence Sets for the Mean of a Multivariate Normal Distribution
Stein, C. (1962) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1962.tb00458.x · Cited by 250
III. The influence of rainfall on the yield of wheat at Rothamsted
Fisher, R. A. (1925) · Philosophical Transactions of the Royal Society of London Series B Containing Papers of a Biological Character · doi:10.1098/rstb.1925.0003 · Cited by 234
The shrinkage of the coefficient of multiple correlation.
Larson, S. C. (1931) · Journal of Educational Psychology · doi:10.1037/h0072400 · Cited by 233
The Choice of Variables in Multiple Regression
Lindley, D. V. (1968) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1968.tb01505.x · Cited by 230
Empirical Bayes on vector observations: An extension of Stein's method
Efron, B., & Morris, C. N. (1972) · Biometrika · doi:10.1093/biomet/59.2.335 · Cited by 224
The Generalized Jackknife Statistic
Strawderman, W. E. (1973) · Journal of Quality Technology · doi:10.1080/00224065.1973.11980580 · Cited by 222
Allocation Rules and Their Error Rates
Hills, M. (1966) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1966.tb00614.x · Cited by 214
The Prediction of Personal Adjustment.
Scates, D. E., & Horst, P. (1942) · Journal of the American Statistical Association · doi:10.2307/2279447 · Cited by 206
Combining Possibly Related Estimation Problems
Efron, B., & Morris, C. N. (1973) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1973.tb00968.x · Cited by 189
Inference in an Authorship Problem
Mosteller, F. C., & Wallace, D. K. (1963) · Journal of the American Statistical Association · doi:10.2307/2283270 · Cited by 187
Topics in the Investigation of Linear Relations Fitted by the Method of Least Squares
Anscombe, F. J. (1967) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1967.tb00672.x · Cited by 141
Some Observations on Robust Estimation
Hogg, R. V. (1967) · Journal of the American Statistical Association · doi:10.1080/01621459.1967.10500924 · Cited by 140
The Generalised Jackknife Statistic.
Springall, A., Gray, H. L., & Schucany, W. R. (1974) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347008 · Cited by 133
The Parameters of Cross-Validation
Herzberg, P. A. (1967) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 110
Testing Transformations to Normality
Atkinson, A. C. (1973) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1973.tb00975.x · Cited by 109
Validity, Reliability, and Baloney
Cureton, E. E. (1950) · Educational and Psychological Measurement · doi:10.1177/001316445001000107 · Cited by 100
Order Statistics Estimators of the Location of the Cauchy Distribution
BARNETT, V. D. (1966) · Journal of the American Statistical Association · doi:10.1080/01621459.1966.10482205 · Cited by 99
Baranchik, A. (1973) · The Annals of Statistics · doi:10.1214/aos/1176342368 · Cited by 82
Criteria for Selection of a Subset Regression: Which One Should Be Used?
Hocking, R. R. (1972) · Technometrics · doi:10.1080/00401706.1972.10488992 · Cited by 78
Polynomial Regression from a Bayesian Approach
Halpern, E. F. (1973) · Journal of the American Statistical Association · doi:10.1080/01621459.1973.10481352 · Cited by 42
King-Hele, D. G., Cook, G., & Scott, D. W. (1969) · Planetary and Space Science · doi:10.1016/0032-0633(69)90185-8 · Cited by 37
Refining the Earth's Pear Shape
King-Hele, D. G., & Cook, G. (1973) · Nature · doi:10.1038/246086a0 · Cited by 33
Statistical Techniques for Diagnosis
Teather, D. (1974) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344551 · Cited by 31
III. Cross-Validation of Item Analyses
Katzell, R. A. (1951) · Educational and Psychological Measurement · doi:10.1177/001316445101100103 · Cited by 26
Analysis of 27 satellite orbits to determine odd zonal harmonics in the geopotential
King-Hele, D. G., & Cook, G. (1974) · Planetary and Space Science · doi:10.1016/0032-0633(74)90138-x · Cited by 24
Wherry, R. J. (1951) · Educational and Psychological Measurement · doi:10.1177/001316445101100104 · Cited by 22
II. Approximate Linear Restraints and Best Predictor Weights
Cureton, E. E. (1951) · Educational and Psychological Measurement · doi:10.1177/001316445101100102 · Cited by 21
Commentary on “Estimation of Error Rates in Discriminant Analysis”
Cochran, W. G. (1968) · Technometrics · doi:10.1080/00401706.1968.10490548 · Cited by 20
Asymptotically Robust Estimators of Location
Birnbaum, A., & Miké, V. (1970) · Journal of the American Statistical Association · doi:10.1080/01621459.1970.10481163 · Cited by 13
Commentary on "Estimation of Error Rates in Discriminant Analysis"
Cochran, W. G. (1968) · Technometrics · doi:10.2307/1266237 · Cited by 12
Research works printed but not linked: 6
- Anderson, 1972, Selection of predictor variables in linear multiple regression
- Mosteller, 1968, Data analysis, including statistics
- Nicholson, 1960, Prediction in future samples
- Nimmo-Smith, 1972, Selecting an estimator from a class of estimator types: An embryo data-analytic technique
- Simon, 1971, Prediction Methods in Criminology. Home Office Research Study, 7
- Stein, 1960, Multiple regression
Cited by
Sorted by citations
When to Use and How to Report the Results of PLS-SEM
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Bayesian Measures of Model Complexity and Fit
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van Der Linde, A. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00353 · Cited by 151
Multimodel Inference: Understanding AIC and BIC in Model Selection
Burnham, K. P., & Anderson, D. R. (2004) · Sociological Methods & Research · doi:10.1177/0049124104268644 · Cited by 11,648
Metadata
- Authors
- Stone, M.
- Affiliations
- University College London (GB)
- Corresponding author
- Stone, M.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1974-01-01
- Volume
- 36
- Issue
- 2
- Pages
- 111-133
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2112081648
- Cited by
- 10,881
- References
- 47
- Citations by year
- 2026: 812 · 2025: 680 · 2024: 654 · 2023: 758 · 2022: 711 · 2021: 828 · 2020: 638 · 2019: 542 · 2018: 436 · 2017: 376 · 2016: 340 · 2015: 350 · 2014: 314 · 2013: 297 · 2012: 285
- FWCI
- 17.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the Royal Statistical Society Series B (Statistical Methodology) (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Keywords
- cross-validation, statistical forecasting, drug prescribing, model selection, linear regression, analysis of variance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review