Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
Top Cited Papers
Open Access
- 1 August 2001
- journal article
- research article
- Published by Institute of Mathematical Statistics in Statistical Science
- Vol. 16 (3) , 199-215
- https://doi.org/10.1214/ss/1009213726
Abstract
There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical community has been committed to the almost exclusive use of data models. This commitment has led to irrelevant theory, questionable conclusions, and has kept statisticians from working on a large range of interesting current problems. Algorithmic modeling, both in theory and practice, has developed rapidly in fields outside statistics. It can be used both on large complex data sets and as a more accurate and informative alternative to data modeling on smaller data sets. If our goal as a field is to use data to solve problems, then we need to move away from exclusive dependence on data models and adopt a more diverse set of tools.This publication has 20 references indexed in Scilit:
- SmcHD1, containing a structural-maintenance-of-chromosomes hinge domain, has a critical role in X inactivationNature Genetics, 2008
- Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)The Annals of Statistics, 2000
- Logicist statistics. I. Models and modelingStatistical Science, 1998
- Arcing classifier (with discussion and a rejoinder by the author)The Annals of Statistics, 1998
- The random subspace method for constructing decision forestsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1998
- Shape Quantization and Recognition with Randomized TreesNeural Computation, 1997
- A Combined Structural and Flexible Functional Approach for Modeling Energy SubstitutionJournal of the American Statistical Association, 1989
- As Others See Us: A Case Study in Path AnalysisJournal of Educational Statistics, 1987
- Estimating Optimal Transformations for Multiple Regression and CorrelationJournal of the American Statistical Association, 1985
- Graphical Methods for Assessing Logistic Regression ModelsJournal of the American Statistical Association, 1984