{"id":"https://openalex.org/W2019697960","doi":"https://doi.org/10.1080/03610910802627055","title":"A Numerical Study of PQL Estimation Biases in Generalized Linear Mixed Models Under Heterogeneity of Random Effects","display_name":"A Numerical Study of PQL Estimation Biases in Generalized Linear Mixed Models Under Heterogeneity of Random Effects","publication_year":2009,"publication_date":"2009-01-31","ids":{"openalex":"https://openalex.org/W2019697960","doi":"https://doi.org/10.1080/03610910802627055","mag":"2019697960"},"language":"en","primary_location":{"id":"doi:10.1080/03610910802627055","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802627055","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/A5030070642","display_name":"Woncheol Jang","orcid":"https://orcid.org/0000-0001-9282-1786"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Woncheol Jang","raw_affiliation_strings":["Department of Epidemiology and Biostatistics , University of Georgia , Athens , Georgia , USA","Department of Epidemiology and Biostatistics University of Georgia  Athens Georgia USA"],"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics , University of Georgia , Athens , Georgia , USA","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"Department of Epidemiology and Biostatistics University of Georgia  Athens Georgia USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090618019","display_name":"Johan Lim","orcid":"https://orcid.org/0000-0002-7565-1954"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Johan Lim","raw_affiliation_strings":["Department of Statistics , Seoul National University , Seoul , Korea","Department of Statistics, Seoul National University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Statistics , Seoul National University , Seoul , Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Statistics, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030070642"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":0.5654,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.6872073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"38","issue":"4","first_page":"692","last_page":"702"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9994000196456909,"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":0.9994000196456909,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9991000294685364,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9975000023841858,"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/random-effects-model","display_name":"Random effects model","score":0.673721194267273},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6329770088195801},{"id":"https://openalex.org/keywords/generalized-linear-mixed-model","display_name":"Generalized linear mixed model","score":0.6123085021972656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5782535076141357},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5548720955848694},{"id":"https://openalex.org/keywords/quasi-likelihood","display_name":"Quasi-likelihood","score":0.5496972799301147},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4671693742275238},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4581316113471985},{"id":"https://openalex.org/keywords/variance-components","display_name":"Variance components","score":0.44362279772758484},{"id":"https://openalex.org/keywords/mixed-model","display_name":"Mixed model","score":0.4343186020851135},{"id":"https://openalex.org/keywords/meta-analysis","display_name":"Meta-analysis","score":0.1672757863998413},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.10401105880737305},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06645858287811279}],"concepts":[{"id":"https://openalex.org/C168743327","wikidata":"https://www.wikidata.org/wiki/Q1826427","display_name":"Random effects model","level":3,"score":0.673721194267273},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6329770088195801},{"id":"https://openalex.org/C153720581","wikidata":"https://www.wikidata.org/wiki/Q5532490","display_name":"Generalized linear mixed model","level":2,"score":0.6123085021972656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5782535076141357},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5548720955848694},{"id":"https://openalex.org/C91025261","wikidata":"https://www.wikidata.org/wiki/Q7269460","display_name":"Quasi-likelihood","level":4,"score":0.5496972799301147},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4671693742275238},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4581316113471985},{"id":"https://openalex.org/C3018076075","wikidata":"https://www.wikidata.org/wiki/Q1826427","display_name":"Variance components","level":2,"score":0.44362279772758484},{"id":"https://openalex.org/C16012445","wikidata":"https://www.wikidata.org/wiki/Q1501135","display_name":"Mixed model","level":2,"score":0.4343186020851135},{"id":"https://openalex.org/C95190672","wikidata":"https://www.wikidata.org/wiki/Q815382","display_name":"Meta-analysis","level":2,"score":0.1672757863998413},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.10401105880737305},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06645858287811279},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910802627055","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910802627055","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":[{"score":0.5099999904632568,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W987144911","https://openalex.org/W1528905581","https://openalex.org/W1968578768","https://openalex.org/W1976058088","https://openalex.org/W1978136073","https://openalex.org/W1982585616","https://openalex.org/W1997921097","https://openalex.org/W2014581807","https://openalex.org/W2017577291","https://openalex.org/W2035196541","https://openalex.org/W2063830806","https://openalex.org/W2077192207","https://openalex.org/W2156499085","https://openalex.org/W2329902133","https://openalex.org/W4236474849","https://openalex.org/W4301861531"],"related_works":["https://openalex.org/W4239710992","https://openalex.org/W2895736713","https://openalex.org/W1551599973","https://openalex.org/W4307324678","https://openalex.org/W2082190293","https://openalex.org/W2021312236","https://openalex.org/W4289422681","https://openalex.org/W225107685","https://openalex.org/W4404985795","https://openalex.org/W3041822475"],"abstract_inverted_index":{"The":[0],"penalized":[1],"quasi-likelihood":[2],"(PQL)":[3],"approach":[4],"is":[5],"the":[6,12,24,37,47,59,71],"most":[7],"common":[8],"estimation":[9],"procedure":[10],"for":[11],"generalized":[13],"linear":[14],"mixed":[15],"model":[16],"(GLMM).":[17],"However,":[18],"it":[19],"has":[20],"been":[21],"noticed":[22],"that":[23,46,70],"PQL":[25,54,78],"tends":[26],"to":[27,58],"underestimate":[28],"variance":[29,50,74],"components":[30],"as":[31,33,80],"well":[32],"regression":[34,62],"coefficients":[35],"in":[36],"previous":[38],"literature.":[39],"In":[40],"this":[41],"article,":[42],"we":[43],"numerically":[44],"show":[45,69],"biases":[48,60,72],"of":[49,61,73],"component":[51,75],"estimates":[52,64,76],"by":[53,65,77],"are":[55],"systematically":[56],"related":[57],"coefficient":[63],"PQL,":[66],"and":[67],"also":[68],"increase":[79],"random":[81],"effects":[82],"become":[83],"more":[84],"heterogeneous.":[85]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}