{"id":"https://openalex.org/W1979736402","doi":"https://doi.org/10.1016/j.csda.2015.04.001","title":"Robust and efficient estimation of effective dose","display_name":"Robust and efficient estimation of effective dose","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W1979736402","doi":"https://doi.org/10.1016/j.csda.2015.04.001","mag":"1979736402"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.csda.2015.04.001","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"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,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5074559589","display_name":"Rohana J. Karunamuni","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Rohana J. Karunamuni","raw_affiliation_string":"Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1","raw_affiliation_strings":["Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1"]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028398394","display_name":"Qingguo Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingguo Tang","raw_affiliation_string":"School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China","raw_affiliation_strings":["School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China"]},{"author_position":"last","author":{"id":"https://openalex.org/A5081435047","display_name":"Bangxin Zhao","orcid":"https://orcid.org/0000-0002-1196-2630"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bangxin Zhao","raw_affiliation_string":"Department of Statistical and Actuarial Sciences, Western University, London, Ontario, Canada N6A 5B7","raw_affiliation_strings":["Department of Statistical and Actuarial Sciences, Western University, London, Ontario, Canada N6A 5B7"]}],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074559589"],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":{"value":3340,"currency":"USD","value_usd":3340,"provenance":"doaj"},"apc_paid":{"value":3340,"currency":"USD","value_usd":3340,"provenance":"doaj"},"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":3,"cited_by_percentile_year":{"min":81,"max":82},"biblio":{"volume":"90","issue":null,"first_page":"47","last_page":"60"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Experimental Design and Optimization Methods","score":0.9992,"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"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Experimental Design and Optimization Methods","score":0.9992,"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"}},{"id":"https://openalex.org/T11443","display_name":"Statistical Process Control in Research and Healthcare Improvement","score":0.9927,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials and Drug Development","score":0.9855,"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":[{"keyword":"efficient estimation","score":0.4321},{"keyword":"dose","score":0.3376}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8071022},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.75704575},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6884424},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.65323985},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.6281192},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.55971664},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5246508},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.49327844},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.48798746},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.45682788},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.45610622},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.4249386},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4198208},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38006103},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3646313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33735257},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.csda.2015.04.001","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"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,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.45,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"11071120"},{"funder":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada","award_id":"7980-09"},{"funder":"https://openalex.org/F4320335982","funder_display_name":"Humanities and Social Science Fund of Ministry of Education of China","award_id":"14YJA910004"}],"referenced_works_count":28,"referenced_works":["https://openalex.org/W1963676859","https://openalex.org/W1968956560","https://openalex.org/W1979500167","https://openalex.org/W1982392262","https://openalex.org/W2007505510","https://openalex.org/W2015450719","https://openalex.org/W2016023898","https://openalex.org/W2025938587","https://openalex.org/W2038336950","https://openalex.org/W2044629648","https://openalex.org/W2057511657","https://openalex.org/W2058247651","https://openalex.org/W2059288868","https://openalex.org/W2067975307","https://openalex.org/W2078912995","https://openalex.org/W2082748942","https://openalex.org/W2084238990","https://openalex.org/W2087166176","https://openalex.org/W2088844710","https://openalex.org/W2092459737","https://openalex.org/W2093064776","https://openalex.org/W2095225664","https://openalex.org/W2103861636","https://openalex.org/W2111060966","https://openalex.org/W2118381969","https://openalex.org/W2118633393","https://openalex.org/W2149569695","https://openalex.org/W2156593932"],"related_works":["https://openalex.org/W1564806038","https://openalex.org/W3150947797","https://openalex.org/W2384198123","https://openalex.org/W2263594168","https://openalex.org/W1523105382","https://openalex.org/W2152101488","https://openalex.org/W3124503859","https://openalex.org/W2050403762","https://openalex.org/W2001933291","https://openalex.org/W3123217622"],"ngrams_url":"https://api.openalex.org/works/W1979736402/ngrams","abstract_inverted_index":{"In":[0,49],"dose\u2013response":[1],"studies,":[2],"experimenters":[3],"are":[4,69,73,85,91,96,103,121,142,152,155,167],"often":[5],"interested":[6,31],"in":[7,25,32,36,105],"estimating":[8,33,109],"the":[9,13,17,39,80,118,124,149],"effective":[10],"dose":[11,14],"EDp,":[12],"at":[15],"which":[16],"probability":[18],"of":[19,47,148],"response":[20],"is":[21,29,42,115],"p,0