{"id":"https://openalex.org/W313178570","doi":"https://doi.org/10.1016/j.aap.2006.02.001","title":"Modeling motor vehicle crashes using Poisson-gamma models: Examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter","display_name":"Modeling motor vehicle crashes using Poisson-gamma models: Examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter","publication_year":2006,"publication_date":"2006-03-21","ids":{"openalex":"https://openalex.org/W313178570","doi":"https://doi.org/10.1016/j.aap.2006.02.001","mag":"313178570","pmid":"https://pubmed.ncbi.nlm.nih.gov/16545328"},"language":"en","primary_location":{"id":"doi:10.1016/j.aap.2006.02.001","doi":"https://doi.org/10.1016/j.aap.2006.02.001","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.aap.2006.02.001","pdf_url":null,"source":{"id":"https://openalex.org/S188336720","display_name":"Accident Analysis & Prevention","issn_l":"0001-4575","issn":["0001-4575","1879-2057"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-scientific","cwts-core","dongbi-b","jufo-3","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Accident Analysis &amp; Prevention","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W313178570"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"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/A5089797666","display_name":"Dominique Lord","orcid":"https://orcid.org/0000-0002-7434-6886","observed_orcids":["https://orcid.org/0000-0002-7434-6886"]},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dominique Lord","raw_affiliation_strings":["Zachry Department of Civil Engineering, TAMU 3136, Texas A&M University, College Station, 77843-3136, USA. d-lord@tamu.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zachry Department of Civil Engineering, TAMU 3136, Texas A&M University, College Station, 77843-3136, USA. d-lord@tamu.edu","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5089797666"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":{"value":4150,"currency":"USD","value_usd":4150},"apc_paid":null,"fwci":77.4473,"has_fulltext":false,"cited_by_count":387,"citation_normalized_percentile":{"value":1.0,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"38","issue":"4","first_page":"751","last_page":"766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.0015999999595806003,"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/T13527","display_name":"Road Transport and Highway Systems","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/poisson-gamma-model","display_name":"Poisson-gamma model","score":0.8849999904632568},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"negative binomial distribution","score":0.9150000214576721},{"id":"https://openalex.org/keywords/dispersion-parameter-estimation","display_name":"dispersion parameter estimation","score":0.8410000205039978},{"id":"https://openalex.org/keywords/small-sample-size","display_name":"small sample size","score":0.8740000128746033},{"id":"https://openalex.org/keywords/overdispersion","display_name":"overdispersion","score":0.8169999718666077},{"id":"https://openalex.org/keywords/method-of-moments","display_name":"method of moments","score":0.6499999761581421},{"id":"https://openalex.org/keywords/weighted-regression","display_name":"weighted regression","score":0.9679999947547913},{"id":"https://openalex.org/keywords/maximum-likelihood-estimation","display_name":"maximum likelihood estimation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/empirical-bayes","display_name":"empirical Bayes","score":0.8859999775886536},{"id":"https://openalex.org/keywords/confidence-intervals","display_name":"confidence intervals","score":0.7269999980926514},{"id":"https://openalex.org/keywords/crash-prediction","display_name":"accident prediction","score":0.4620000123977661},{"id":"https://openalex.org/keywords/highway-safety","display_name":"highway safety","score":0.8130000233650208}],"concepts":[{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7739846706390381},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.7648240327835083},{"id":"https://openalex.org/C132480984","wikidata":"https://www.wikidata.org/wiki/Q2034239","display_name":"Goodness of fit","level":2,"score":0.6945902109146118},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.6551802158355713},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.6418519020080566},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6001272201538086},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5354585647583008},{"id":"https://openalex.org/C177562468","wikidata":"https://www.wikidata.org/wiki/Q182893","display_name":"Dispersion (optics)","level":2,"score":0.5234453082084656},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5176489949226379},{"id":"https://openalex.org/C3017903533","wikidata":"https://www.wikidata.org/wiki/Q9687","display_name":"Motor vehicle crash","level":4,"score":0.5090293884277344},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.4883992075920105},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.4607475996017456},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.43175801634788513},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.43019479513168335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.401878297328949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3774707615375519},{"id":"https://openalex.org/C3017944768","wikidata":"https://www.wikidata.org/wiki/Q1450463","display_name":"Poison control","level":2,"score":0.34528636932373047},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.1352008581161499},{"id":"https://openalex.org/C190385971","wikidata":"https://www.wikidata.org/wiki/Q373494","display_name":"Injury prevention","level":3,"score":0.10422113537788391},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08246412873268127},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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":[{"descriptor_ui":"D000063","descriptor_name":"Accidents, Traffic","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","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":true},{"descriptor_ui":"D016001","descriptor_name":"Confidence Intervals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016012","descriptor_name":"Poisson Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018401","descriptor_name":"Sample Size","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.1016/j.aap.2006.02.001","doi":"https://doi.org/10.1016/j.aap.2006.02.001","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.aap.2006.02.001","pdf_url":null,"source":{"id":"https://openalex.org/S188336720","display_name":"Accident Analysis & Prevention","issn_l":"0001-4575","issn":["0001-4575","1879-2057"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-scientific","cwts-core","dongbi-b","jufo-3","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Accident Analysis &amp; Prevention","raw_type":"journal-article"},{"id":"pmid:16545328","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/16545328","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":"Accident; analysis and prevention","raw_type":"Journal Article"},{"id":"mag:313178570","doi":null,"is_oa":false,"landing_page_url":"https://trid.trb.org/view.aspx?id=777399","pdf_url":null,"source":{"id":"https://openalex.org/S4306533223","display_name":"Transportation Research Board 85th Annual MeetingTransportation Research Board","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Transportation Research Board 85th Annual MeetingTransportation Research Board","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.398.1586","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.398.1586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.460.368","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.460.368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ceprofs.civil.tamu.edu/dlord/Papers/DLord_LMP_and_Dispersion_Parameter.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W9032326","https://openalex.org/W29755948","https://openalex.org/W237767408","https://openalex.org/W583046108","https://openalex.org/W856761652","https://openalex.org/W1528905581","https://openalex.org/W1539778568","https://openalex.org/W1556655499","https://openalex.org/W1560564256","https://openalex.org/W1586015540","https://openalex.org/W1916436209","https://openalex.org/W1963495107","https://openalex.org/W1964744847","https://openalex.org/W1969953591","https://openalex.org/W1972707698","https://openalex.org/W1973628995","https://openalex.org/W1975385327","https://openalex.org/W1976961608","https://openalex.org/W1979655209","https://openalex.org/W1994839527","https://openalex.org/W1997363842","https://openalex.org/W1997960054","https://openalex.org/W2001768421","https://openalex.org/W2003270497","https://openalex.org/W2013721546","https://openalex.org/W2017259260","https://openalex.org/W2020802452","https://openalex.org/W2022982503","https://openalex.org/W2026154856","https://openalex.org/W2027874981","https://openalex.org/W2028216950","https://openalex.org/W2035983506","https://openalex.org/W2036681942","https://openalex.org/W2047905873","https://openalex.org/W2060817938","https://openalex.org/W2062603300","https://openalex.org/W2065454927","https://openalex.org/W2068026461","https://openalex.org/W2070047061","https://openalex.org/W2074818071","https://openalex.org/W2078409719","https://openalex.org/W2082178515","https://openalex.org/W2083126399","https://openalex.org/W2085309210","https://openalex.org/W2099362404","https://openalex.org/W2104115740","https://openalex.org/W2115855457","https://openalex.org/W2116545394","https://openalex.org/W2125961882","https://openalex.org/W2132780471","https://openalex.org/W2140648520","https://openalex.org/W2140908056","https://openalex.org/W2150836500","https://openalex.org/W2153478504","https://openalex.org/W2155116765","https://openalex.org/W2162595628","https://openalex.org/W2167839827","https://openalex.org/W2170177776","https://openalex.org/W2294691689","https://openalex.org/W2316224434","https://openalex.org/W2326040775","https://openalex.org/W2463051692","https://openalex.org/W3015463134","https://openalex.org/W4301861531","https://openalex.org/W4302853952","https://openalex.org/W6632219993","https://openalex.org/W6675767960"],"related_works":["https://openalex.org/W2097725918","https://openalex.org/W1978803591","https://openalex.org/W2075273659","https://openalex.org/W2243647137","https://openalex.org/W2163205866","https://openalex.org/W2072732498","https://openalex.org/W2177484855"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":32},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":24},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":19},{"year":2014,"cited_by_count":15},{"year":2013,"cited_by_count":30},{"year":2012,"cited_by_count":14}],"updated_date":"2026-11-15T12:55:33.944570","created_date":"2016-06-24T00:00:00"}
