{"id":"https://openalex.org/W2514149607","doi":null,"title":"K-Fold Cross-Validation is Superior to Split Sample Validation for Risk Adjustment Models","display_name":"K-Fold Cross-Validation is Superior to Split Sample Validation for Risk Adjustment Models","publication_year":2013,"publication_date":"2013-06-07","ids":{"openalex":"https://openalex.org/W2514149607","mag":"2514149607"},"language":"en","primary_location":{"id":"pmh:oai:RePEc:bos:wpaper:wp2013-026","doi":null,"is_oa":false,"landing_page_url":"http://www.bu.edu/econ/files/2016/01/Ellis_Mookim_R2paper_20130605.pdf","pdf_url":"http://www.bu.edu/econ/files/2016/01/Ellis_Mookim_R2paper_20130605.pdf","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032378120","display_name":"Randall P. Ellis","orcid":"https://orcid.org/0000-0003-2176-5347","observed_orcids":["https://orcid.org/0000-0003-2176-5347"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Randall P. Ellis","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2176-5347","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085055285","display_name":"Pooja G. Mookim","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pooja G. Mookim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.4560999870300293,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.4560999870300293,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13141","display_name":"Statistical Methods and Applications","score":0.15639999508857727,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14374","display_name":"Statistical Methods in Epidemiology","score":0.11140000075101852,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/k-fold-cross-validation","display_name":"k-fold cross-validation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/split-sample-validation","display_name":"split-sample validation","score":0.7419999837875366},{"id":"https://openalex.org/keywords/risk-adjustment-models","display_name":"risk adjustment models","score":0.9909999966621399},{"id":"https://openalex.org/keywords/predictive-validity","display_name":"predictive validity","score":0.7730000019073486},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.984000027179718},{"id":"https://openalex.org/keywords/goodness-of-fit-measures","display_name":"goodness-of-fit measures","score":0.7770000100135803},{"id":"https://openalex.org/keywords/claims-data","display_name":"claims data","score":0.5180000066757202},{"id":"https://openalex.org/keywords/sample-size-bias","display_name":"sample size bias","score":0.5149999856948853},{"id":"https://openalex.org/keywords/estimation-algorithms","display_name":"estimation algorithms","score":0.36500000953674316}],"concepts":[{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.8091189861297607},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7908374667167664},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5941681861877441},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5506585836410522},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5472691655158997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4999063014984131},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.44993945956230164},{"id":"https://openalex.org/C53942344","wikidata":"https://www.wikidata.org/wiki/Q951651","display_name":"Fold (higher-order function)","level":2,"score":0.428072065114975},{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.42381149530410767},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3502785861492157},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3445541560649872},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28920429944992065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18044278025627136},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:RePEc:bos:wpaper:wp2013-026","doi":null,"is_oa":false,"landing_page_url":"http://www.bu.edu/econ/files/2016/01/Ellis_Mookim_R2paper_20130605.pdf","pdf_url":"http://www.bu.edu/econ/files/2016/01/Ellis_Mookim_R2paper_20130605.pdf","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"},{"id":"mag:2514149607","doi":null,"is_oa":false,"landing_page_url":"https://econpapers.repec.org/paper/boswpaper/wp2013-026.htm","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"RePEc: Research Papers in Economics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1479855771","https://openalex.org/W1520227503","https://openalex.org/W1936079746","https://openalex.org/W1959486990","https://openalex.org/W1969430117","https://openalex.org/W1986666737","https://openalex.org/W2031614350","https://openalex.org/W2037164372","https://openalex.org/W2077268598","https://openalex.org/W2112081648","https://openalex.org/W2124181495","https://openalex.org/W2130633358","https://openalex.org/W3122533613","https://openalex.org/W3123574146"],"related_works":["https://openalex.org/W7099072099","https://openalex.org/W2971191549","https://openalex.org/W3119731907","https://openalex.org/W7167263655","https://openalex.org/W7120808210","https://openalex.org/W7220387687","https://openalex.org/W4252433881","https://openalex.org/W4416020012","https://openalex.org/W2624005943","https://openalex.org/W2156832033"],"abstract_inverted_index":{"This":[0],"paper":[1],"examines":[2],"cross-validation":[3,24,102],"techniques,":[4],"with":[5,37],"a":[6,29,48,105,129],"particular":[7],"focus":[8],"on":[9,85,95,158],"assessing":[10],"thepredictive":[11],"validity":[12],"of":[13,47,66,68,100,118],"risk":[14,39],"adjustment":[15,40],"models":[16,41,123],"as":[17],"commonly":[18],"estimated.":[19],"We":[20],"validate":[21],"that":[22,35,57,143,153],"K-Fold":[23,60],"is":[25,55,109],"more":[26],"efficient":[27],"than":[28,137],"50-50":[30],"split":[31],"sample":[32,86,125,135],"and":[33,63,79,116,124,149],"illustrate":[34],"overfitting":[36],"rich":[38],"remains":[42],"meaningful":[43],"even":[44],"in":[45,88,132,147],"samples":[46],"million":[49],"observations.":[50],"A":[51],"new":[52],"estimation":[53],"algorithm":[54,146],"described":[56],"efficiently":[58],"calculates":[59],"cross-validated":[61],"R-squared":[62],"other":[64],"measures":[65],"goodness":[67],"fit":[69],"using":[70,104],"only":[71],"three":[72],"(XXX":[73],"verify)":[74],"passes":[75],"through":[76],"the":[77,89,113,145],"data,":[78],"hence":[80],"can":[81,154],"be":[82,155],"applied":[83],"easily":[84,156],"sizes":[87,136],"millions":[90],"without":[91],"sorting":[92],"or":[93],"relying":[94],"repeated":[96],"split-sample":[97],"techniques.":[98],"Analysis":[99],"K-fold":[101],"results":[103],"large":[106,134],"claims":[107],"dataset":[108],"used":[110,157],"to":[111],"calculate":[112],"standard":[114],"deviation":[115],"bias":[117,131],"fitted":[119],"R-squares":[120],"for":[121],"different":[122],"sizes,":[126],"which":[127],"have":[128],"larger":[130],"moderately":[133],"most":[138],"researchers":[139],"would":[140],"realize.":[141],"Programs":[142],"implement":[144],"SAS":[148],"STATA":[150],"are":[151],"presented":[152],"any":[159],"sample.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2016-09-16T00:00:00"}