{"id":"https://openalex.org/W2074900200","doi":"https://doi.org/10.1080/03610910903480834","title":"Semiparametric Negative Binomial Regression Models","display_name":"Semiparametric Negative Binomial Regression Models","publication_year":2010,"publication_date":"2010-02-19","ids":{"openalex":"https://openalex.org/W2074900200","doi":"https://doi.org/10.1080/03610910903480834","mag":"2074900200"},"language":"en","primary_location":{"id":"doi:10.1080/03610910903480834","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903480834","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5086251816","display_name":"Chin\u2010Shang Li","orcid":"https://orcid.org/0000-0002-0054-4476"},"institutions":[{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]},{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chin-Shang Li","raw_affiliation_strings":["University of California","Department of Public Health Sciences, Division of Biostatistics , University of California , Davis, California, USA"],"affiliations":[{"raw_affiliation_string":"University of California","institution_ids":["https://openalex.org/I2803209242"]},{"raw_affiliation_string":"Department of Public Health Sciences, Division of Biostatistics , University of California , Davis, California, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086251816"],"corresponding_institution_ids":["https://openalex.org/I2803209242","https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":0.451,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73228377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":"3","first_page":"475","last_page":"486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9954000115394592,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9912999868392944,"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/overdispersion","display_name":"Overdispersion","score":0.8816543817520142},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.8705990314483643},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6576359272003174},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6194548606872559},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.6178409457206726},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5630980730056763},{"id":"https://openalex.org/keywords/quasi-likelihood","display_name":"Quasi-likelihood","score":0.5608444213867188},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5086784958839417},{"id":"https://openalex.org/keywords/poisson-regression","display_name":"Poisson regression","score":0.48846545815467834},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.47120019793510437},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.4516443908214569},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4407809376716614},{"id":"https://openalex.org/keywords/goodness-of-fit","display_name":"Goodness of fit","score":0.4264981746673584},{"id":"https://openalex.org/keywords/generalized-linear-model","display_name":"Generalized linear model","score":0.42618328332901},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.41369202733039856},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.39982035756111145},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.06911417841911316}],"concepts":[{"id":"https://openalex.org/C117236510","wikidata":"https://www.wikidata.org/wiki/Q7113620","display_name":"Overdispersion","level":4,"score":0.8816543817520142},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.8705990314483643},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6576359272003174},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6194548606872559},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.6178409457206726},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5630980730056763},{"id":"https://openalex.org/C91025261","wikidata":"https://www.wikidata.org/wiki/Q7269460","display_name":"Quasi-likelihood","level":4,"score":0.5608444213867188},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5086784958839417},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.48846545815467834},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.47120019793510437},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.4516443908214569},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4407809376716614},{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.4264981746673584},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.42618328332901},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.41369202733039856},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.39982035756111145},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.06911417841911316},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910903480834","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910903480834","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320893","display_name":"Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale","ror":"https://ror.org/02vjkv261"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W101236184","https://openalex.org/W1423766661","https://openalex.org/W1480101757","https://openalex.org/W1487825358","https://openalex.org/W1490266132","https://openalex.org/W1528905581","https://openalex.org/W1552247668","https://openalex.org/W1976601779","https://openalex.org/W1982142842","https://openalex.org/W1986096508","https://openalex.org/W1990420052","https://openalex.org/W1993399106","https://openalex.org/W2001409669","https://openalex.org/W2027106381","https://openalex.org/W2064385888","https://openalex.org/W2065540158","https://openalex.org/W2081969704","https://openalex.org/W2083610611","https://openalex.org/W2084371789","https://openalex.org/W2085309210","https://openalex.org/W2091461986","https://openalex.org/W2124470163","https://openalex.org/W2162870748","https://openalex.org/W2182274314","https://openalex.org/W2396900654","https://openalex.org/W2567032824","https://openalex.org/W2797463641","https://openalex.org/W2797583072","https://openalex.org/W4230615526","https://openalex.org/W4234627034","https://openalex.org/W4237622357","https://openalex.org/W4237967802","https://openalex.org/W4238080384","https://openalex.org/W4242488246","https://openalex.org/W4247395064","https://openalex.org/W4253560234","https://openalex.org/W4299603473","https://openalex.org/W4301861531","https://openalex.org/W4302853952"],"related_works":["https://openalex.org/W2189104843","https://openalex.org/W2885569989","https://openalex.org/W3178810070","https://openalex.org/W2765416750","https://openalex.org/W3134768068","https://openalex.org/W2081430863","https://openalex.org/W4390402773","https://openalex.org/W2293066536","https://openalex.org/W2899996524","https://openalex.org/W3038787011"],"abstract_inverted_index":{"Negative-binomial":[0],"(NB)":[1],"regression":[2],"models":[3],"have":[4,32],"been":[5,33],"widely":[6],"used":[7,41],"for":[8,23,28],"analysis":[9],"of":[10,51,73,78,91],"count":[11],"data":[12],"displaying":[13],"substantial":[14],"overdispersion":[15],"(extra-Poisson":[16],"variation).":[17],"However,":[18],"no":[19],"formal":[20],"lack-of-fit":[21],"tests":[22],"a":[24,29,36,48,63,74],"postulated":[25,75],"parametric":[26,38,76],"model":[27,43],"covariate":[30,45,80],"effect":[31,46],"proposed.":[34],"Therefore,":[35],"flexible":[37],"procedure":[39],"is":[40,67],"to":[42,69,86],"the":[44,59,71,79,88,92],"as":[47],"linear":[49],"combination":[50],"fixed-knot":[52],"cubic":[53],"basis":[54],"splines":[55],"or":[56],"B-splines.":[57],"Within":[58],"proposed":[60,93],"modeling":[61],"framework,":[62],"log-likelihood":[64],"ratio":[65],"test":[66],"constructed":[68],"evaluate":[70],"adequacy":[72],"form":[77],"effect.":[81],"Simulation":[82],"experiments":[83],"are":[84],"conducted":[85],"study":[87],"power":[89],"performance":[90],"test.":[94]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}