{"id":"https://openalex.org/W2483634708","doi":"https://doi.org/10.1080/03610918.2015.1062103","title":"A statistical software procedure for exact parametric and nonparametric likelihood-ratio tests for two-sample comparisons","display_name":"A statistical software procedure for exact parametric and nonparametric likelihood-ratio tests for two-sample comparisons","publication_year":2015,"publication_date":"2015-11-12","ids":{"openalex":"https://openalex.org/W2483634708","doi":"https://doi.org/10.1080/03610918.2015.1062103","mag":"2483634708"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2015.1062103","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1062103","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/A5100740575","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0002-8703-3678"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024763537","display_name":"Albert Vexler","orcid":"https://orcid.org/0000-0001-9552-4082"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Albert Vexler","raw_affiliation_strings":["Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069146590","display_name":"Alan D. Hutson","orcid":"https://orcid.org/0000-0002-7353-5650"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Hutson","raw_affiliation_strings":["Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036953947","display_name":"Xiwei Chen","orcid":"https://orcid.org/0000-0003-1868-8387"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiwei Chen","raw_affiliation_strings":["Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024763537"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18436353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"46","issue":"4","first_page":"2829","last_page":"2841"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9987999796867371,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9987999796867371,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9983000159263611,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bonferroni-correction","display_name":"Bonferroni correction","score":0.741593062877655},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.6179470419883728},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5793885588645935},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.5739678144454956},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5658620595932007},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.5338189601898193},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5032791495323181},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4990653991699219},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.49538934230804443},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49163299798965454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4796714782714844},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.469192236661911},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4633724093437195},{"id":"https://openalex.org/keywords/ratio-test","display_name":"Ratio test","score":0.43318092823028564},{"id":"https://openalex.org/keywords/empirical-likelihood","display_name":"Empirical likelihood","score":0.42761799693107605},{"id":"https://openalex.org/keywords/multiple-comparisons-problem","display_name":"Multiple comparisons problem","score":0.42212215065956116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40126845240592957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15018543601036072}],"concepts":[{"id":"https://openalex.org/C127808970","wikidata":"https://www.wikidata.org/wiki/Q385989","display_name":"Bonferroni correction","level":2,"score":0.741593062877655},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.6179470419883728},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5793885588645935},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.5739678144454956},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5658620595932007},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.5338189601898193},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5032791495323181},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4990653991699219},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.49538934230804443},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49163299798965454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4796714782714844},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.469192236661911},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4633724093437195},{"id":"https://openalex.org/C192914289","wikidata":"https://www.wikidata.org/wiki/Q165638","display_name":"Ratio test","level":2,"score":0.43318092823028564},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.42761799693107605},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.42212215065956116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40126845240592957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15018543601036072},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2015.1062103","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1062103","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":[{"display_name":"Peace, Justice and strong institutions","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1822001419","https://openalex.org/W1930623320","https://openalex.org/W1984140225","https://openalex.org/W1985751213","https://openalex.org/W1997837534","https://openalex.org/W2045638068","https://openalex.org/W2054682870","https://openalex.org/W2064379684","https://openalex.org/W2065949564","https://openalex.org/W2067104085","https://openalex.org/W2084491844","https://openalex.org/W2086573335","https://openalex.org/W2087783176","https://openalex.org/W2165667160","https://openalex.org/W2266265979","https://openalex.org/W2317320087","https://openalex.org/W2409412004","https://openalex.org/W2506075071","https://openalex.org/W2582743722"],"related_works":["https://openalex.org/W2093104131","https://openalex.org/W2333750400","https://openalex.org/W2034495139","https://openalex.org/W2104806243","https://openalex.org/W2467227750","https://openalex.org/W4293336298","https://openalex.org/W4250330777","https://openalex.org/W2067937539","https://openalex.org/W2072145370","https://openalex.org/W2034517628"],"abstract_inverted_index":{"Two-sample":[0],"comparisons":[1,140],"belonging":[2],"to":[3,24,38,105,136,175],"basic":[4],"class":[5],"of":[6,32,50,78,110,182],"statistical":[7,18],"inference":[8],"are":[9,36,53],"extensively":[10],"applied":[11],"in":[12],"practice.":[13],"There":[14],"is":[15],"a":[16,62,171],"rich":[17],"literature":[19],"regarding":[20],"different":[21],"parametric":[22],"methods":[23],"address":[25],"these":[26],"problems.":[27],"In":[28,45,56],"this":[29,57],"context,":[30],"most":[31],"the":[33,47,67,72,84,101,107,111,117,127,131,138,142,146,148,152,158,183],"powerful":[34],"techniques":[35],"assumed":[37],"be":[39,96],"based":[40,65],"on":[41,66],"normally":[42],"distributed":[43],"populations.":[44],"practice,":[46],"alternative":[48],"distributions":[49],"compared":[51],"samples":[52,112],"commonly":[54],"unknown.":[55],"case,":[58],"one":[59],"can":[60,95],"propose":[61,116],"combined":[63,150],"test":[64,74,87,144],"following":[68],"decision":[69],"rules:":[70],"(a)":[71,92],"likelihood-ratio":[73],"(LRT)":[75],"for":[76,88],"equality":[77],"two":[79],"normal":[80],"populations":[81],"and":[82,93,170,179],"(b)":[83,94],"Shapiro\u2013Wilk":[85],"(S-W)":[86],"normality.":[89],"The":[90],"rules":[91],"merged":[97],"by,":[98],"e.g.,":[99],"using":[100,141],"Bonferroni":[102],"correction":[103],"technique":[104],"offer":[106],"correct":[108],"comparison":[109],"distribution.":[113],"Alternatively,":[114],"we":[115],"exact":[118,143],"density-based":[119],"empirical":[120],"likelihood":[121],"(DBEL)":[122],"ratio":[123,162],"test.":[124,163],"We":[125,164],"develop":[126],"tsc":[128],"package":[129,134],"as":[130,155,157],"first":[132],"R":[133],"available":[135],"perform":[137],"two-sample":[139],"procedures:":[145],"LRT;":[147],"LRT":[149],"with":[151],"S-W":[153],"test;":[154],"well":[156],"newly":[159],"developed":[160,184],"DBEL":[161],"demonstrate":[165],"Monte":[166],"Carlo":[167],"(MC)":[168],"results":[169],"real":[172],"data":[173],"example":[174],"show":[176],"an":[177],"efficiency":[178],"excellent":[180],"applicability":[181],"procedure.":[185]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
