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- One_in_ten_rule abstract "In statistics, the one in ten rule is a rule of thumb for how many predictors can be derived from data when doing regression analysis (in particular proportional hazards models) without risk of overfitting. The rule states that one predictive variable can be studied for every ten events.For example, if a sample of 200 patients are studied and 20 patients die during the study, only two pre-specified predictors can reliably be fitted to the total data. If more are fitted, overfitting is likely and the results will not predict well outside the training data. It is not uncommon to see the 1:10 rule violated in fields with many variables (e.g. gene expression studies in cancer), decreasing the confidence in reported findings.The one in ten rule is a minimum; a \"one in 20 rule\" has been suggested, indicating the need for shrinkage of regression coefficients, and a \"one in 50 rule\" for stepwise selection with the default p-value of 5%.".
- One_in_ten_rule wikiPageID "40765972".
- One_in_ten_rule wikiPageLength "2477".
- One_in_ten_rule wikiPageOutDegree "10".
- One_in_ten_rule wikiPageRevisionID "699174657".
- One_in_ten_rule wikiPageWikiLink Category:Rules_of_thumb.
- One_in_ten_rule wikiPageWikiLink Category:Statistics.
- One_in_ten_rule wikiPageWikiLink Overfitting.
- One_in_ten_rule wikiPageWikiLink P-value.
- One_in_ten_rule wikiPageWikiLink Proportional_hazards_model.
- One_in_ten_rule wikiPageWikiLink Regression_analysis.
- One_in_ten_rule wikiPageWikiLink Rule_of_thumb.
- One_in_ten_rule wikiPageWikiLink Shrinkage_(statistics).
- One_in_ten_rule wikiPageWikiLink Statistics.
- One_in_ten_rule wikiPageWikiLink Stepwise_regression.
- One_in_ten_rule wikiPageWikiLinkText "One in ten rule".
- One_in_ten_rule wikiPageUsesTemplate Template:Orphan.
- One_in_ten_rule wikiPageUsesTemplate Template:Reflist.
- One_in_ten_rule subject Category:Rules_of_thumb.
- One_in_ten_rule subject Category:Statistics.
- One_in_ten_rule hypernym Rule.
- One_in_ten_rule type Country.
- One_in_ten_rule comment "In statistics, the one in ten rule is a rule of thumb for how many predictors can be derived from data when doing regression analysis (in particular proportional hazards models) without risk of overfitting. The rule states that one predictive variable can be studied for every ten events.For example, if a sample of 200 patients are studied and 20 patients die during the study, only two pre-specified predictors can reliably be fitted to the total data.".
- One_in_ten_rule label "One in ten rule".
- One_in_ten_rule sameAs Q17104887.
- One_in_ten_rule sameAs m.0y69x3g.
- One_in_ten_rule sameAs Q17104887.
- One_in_ten_rule wasDerivedFrom One_in_ten_rule?oldid=699174657.
- One_in_ten_rule isPrimaryTopicOf One_in_ten_rule.