{"id":"https://openalex.org/W2799760396","doi":"https://doi.org/10.1002/hec.3651","title":"Analyzing medical costs with time\u2010dependent treatment: The nested g\u2010formula","display_name":"Analyzing medical costs with time\u2010dependent treatment: The nested g\u2010formula","publication_year":2018,"publication_date":"2018-04-16","ids":{"openalex":"https://openalex.org/W2799760396","doi":"https://doi.org/10.1002/hec.3651","mag":"2799760396","pmid":"https://pubmed.ncbi.nlm.nih.gov/29663579","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/8218600"},"language":"en","primary_location":{"id":"doi:10.1002/hec.3651","doi":"https://doi.org/10.1002/hec.3651","is_oa":false,"landing_page_url":"https://doi.org/10.1002/hec.3651","pdf_url":null,"source":{"id":"https://openalex.org/S145200904","display_name":"Health Economics","issn_l":"1057-9230","issn":["1057-9230","1099-1050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","fnege-2","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Health Economics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8218600","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000698542","display_name":"Andrew J. Spieker","orcid":"https://orcid.org/0000-0002-0548-8311","observed_orcids":["https://orcid.org/0000-0002-0548-8311"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Spieker","raw_affiliation_strings":["Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania"],"raw_orcid":"https://orcid.org/0000-0002-0548-8311","affiliations":[{"raw_affiliation_string":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102729009","display_name":"Jason A. Roy","orcid":"https://orcid.org/0000-0003-4237-0504","observed_orcids":["https://orcid.org/0000-0003-4237-0504"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Roy","raw_affiliation_strings":["Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038915889","display_name":"Nandita Mitra","orcid":"https://orcid.org/0000-0002-7714-3910","observed_orcids":["https://orcid.org/0000-0002-7714-3910"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nandita Mitra","raw_affiliation_strings":["Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5000698542"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":{"value":4050,"currency":"USD","value_usd":4050},"apc_paid":null,"fwci":0.8299,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7507608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"27","issue":"7","first_page":"1063","last_page":"1073"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9980000257492065,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9980000257492065,"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/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.0003000000142492354,"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/health-care-costs","display_name":"health care costs","score":0.7710000276565552},{"id":"https://openalex.org/keywords/time-dependent-treatment","display_name":"time-dependent treatment","score":0.7260000109672546},{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.44699999690055847},{"id":"https://openalex.org/keywords/cancer-treatment-costs","display_name":"cancer treatment costs","score":0.9430000185966492}],"concepts":[{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.7418345808982849},{"id":"https://openalex.org/C35981017","wikidata":"https://www.wikidata.org/wiki/Q6060409","display_name":"Inverse probability","level":4,"score":0.6250665187835693},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5914340615272522},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5688586235046387},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5258619785308838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5117108821868896},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.47570616006851196},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.41294947266578674},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36481979489326477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36449387669563293},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3307191729545593},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.321883887052536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3141413629055023},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.12297022342681885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11512112617492676},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.0}],"mesh":[{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004470","descriptor_name":"Economics, Medical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011640","descriptor_name":"Public Policy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017048","descriptor_name":"Health Care Costs","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1002/hec.3651","doi":"https://doi.org/10.1002/hec.3651","is_oa":false,"landing_page_url":"https://doi.org/10.1002/hec.3651","pdf_url":null,"source":{"id":"https://openalex.org/S145200904","display_name":"Health Economics","issn_l":"1057-9230","issn":["1057-9230","1099-1050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","fnege-2","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Health Economics","raw_type":"journal-article"},{"id":"pmid:29663579","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29663579","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Health economics","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8218600","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8218600","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Health Econ","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8218600","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8218600","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Health Econ","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5683000087738037}],"study_designs":[],"awards":[{"id":"https://openalex.org/G3067028087","display_name":"Non-Parametric Bayesian Methods for Causal Inference","funder_award_id":"R01GM112327","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1969855952","https://openalex.org/W2064097590","https://openalex.org/W2068957247","https://openalex.org/W2082299845","https://openalex.org/W2124371789","https://openalex.org/W2139963961","https://openalex.org/W2140752328","https://openalex.org/W2159198921","https://openalex.org/W2222353330","https://openalex.org/W4298872162"],"related_works":["https://openalex.org/W3080314035","https://openalex.org/W2617980253","https://openalex.org/W1982686337","https://openalex.org/W7027310421","https://openalex.org/W7166728128","https://openalex.org/W1973855943","https://openalex.org/W4300982103","https://openalex.org/W2141508928","https://openalex.org/W4225141155","https://openalex.org/W2078492238"],"abstract_inverted_index":{"As":[0],"medical":[1],"expenses":[2],"continue":[3],"to":[4,7,19,33,42,47,66,83,120,127,158,169,193],"rise,":[5],"methods":[6,195],"properly":[8],"analyze":[9],"cost":[10,38,198],"outcomes":[11],"are":[12],"becoming":[13],"of":[14,37,56,62,101,114,174],"increasing":[15],"relevance":[16],"when":[17,104,176,196],"seeking":[18],"compare":[20,48,84],"average":[21],"costs":[22,50,86,134],"across":[23],"treatments.":[24,138],"Inverse":[25],"probability":[26],"weighted":[27],"regression":[28],"models":[29],"have":[30],"been":[31],"developed":[32],"address":[34],"the":[35,54,96,112,147,153,171],"challenge":[36],"censoring":[39],"in":[40],"order":[41],"identify":[43],"intent-to-treat":[44,144],"effects":[45,145,150],"(i.e.,":[46],"mean":[49,85],"between":[51,87,178],"groups":[52],"on":[53],"basis":[55],"their":[57,67],"initial":[58],"treatment":[59,68,92],"assignment,":[60],"irrespective":[61],"any":[63],"subsequent":[64],"changes":[65],"status).":[69],"In":[70],"this":[71,102,115],"paper,":[72],"we":[73],"describe":[74],"a":[75,118,128,189],"nested":[76,154,183],"g-computation":[77],"procedure":[78],"that":[79,141],"can":[80,156],"be":[81,186],"used":[82],"two":[88,180],"or":[89],"more":[90],"time-varying":[91],"regimes.":[93],"We":[94,110],"highlight":[95],"relative":[97],"advantages":[98],"and":[99],"limitations":[100],"approach":[103,116],"compared":[105],"with":[106,136],"existing":[107,194],"regression-based":[108],"models.":[109],"illustrate":[111],"utility":[113],"as":[117,188],"means":[119],"inform":[121],"public":[122],"policy":[123],"by":[124,133,152],"applying":[125],"it":[126,166],"simulated":[129],"data":[130],"example":[131],"motivated":[132],"associated":[135],"cancer":[137],"Simulations":[139],"confirm":[140],"inference":[142,175],"regarding":[143,162],"versus":[146],"joint":[148],"causal":[149],"estimated":[151],"g-formula":[155,184],"lead":[157],"markedly":[159],"different":[160],"conclusions":[161],"differential":[163],"costs.":[164],"Therefore,":[165],"is":[167],"essential":[168],"prespecify":[170],"desired":[172],"target":[173],"choosing":[177],"these":[179],"frameworks.":[181],"The":[182],"should":[185],"considered":[187],"useful,":[190],"complementary":[191],"tool":[192],"analyzing":[197],"outcomes.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2018-05-17T00:00:00"}
