{"id":"https://openalex.org/W91585358","doi":null,"title":"Assessing the efficacy of the trim and fill method in adjusting for publication bias in meta analysis","display_name":"Assessing the efficacy of the trim and fill method in adjusting for publication bias in meta analysis","publication_year":2012,"publication_date":"2012-02-21","ids":{"openalex":"https://openalex.org/W91585358","mag":"91585358"},"language":"en","primary_location":{"id":"mag:91585358","doi":null,"is_oa":false,"landing_page_url":"http://irep.iium.edu.my/25593/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5034810549","display_name":"Nik Ruzni Nik Idris","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nik Ruzni Nik Idris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083385346","display_name":"Norraida Sarudin","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Norraida Sarudin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01732227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.9994999766349792,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":9.999999747378752e-05,"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/T10102","display_name":"scientometrics and bibliometrics research","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3309","display_name":"Library and Information Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/publication-bias","display_name":"publication bias","score":0.8650000095367432},{"id":"https://openalex.org/keywords/funnel-plot-asymmetry","display_name":"funnel plot asymmetry","score":0.8330000042915344},{"id":"https://openalex.org/keywords/meta-analysis","display_name":"meta-analysis","score":0.527999997138977},{"id":"https://openalex.org/keywords/standardized-mean-difference","display_name":"standardized mean difference","score":0.8370000123977661},{"id":"https://openalex.org/keywords/continuous-outcomes","display_name":"continuous outcomes","score":0.7049999833106995},{"id":"https://openalex.org/keywords/missing-studies","display_name":"missing studies","score":0.5839999914169312},{"id":"https://openalex.org/keywords/confidence-interval-coverage","display_name":"confidence interval coverage","score":0.7990000247955322},{"id":"https://openalex.org/keywords/simulation-study","display_name":"simulation study","score":0.640999972820282}],"concepts":[{"id":"https://openalex.org/C2780439572","wikidata":"https://www.wikidata.org/wiki/Q919364","display_name":"Publication bias","level":3,"score":0.8797768354415894},{"id":"https://openalex.org/C95190672","wikidata":"https://www.wikidata.org/wiki/Q815382","display_name":"Meta-analysis","level":2,"score":0.8494758009910583},{"id":"https://openalex.org/C82605166","wikidata":"https://www.wikidata.org/wiki/Q967190","display_name":"Funnel plot","level":4,"score":0.809980034828186},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6202607154846191},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.42840713262557983},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3673090934753418},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3415166735649109},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15831926465034485}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:91585358","doi":null,"is_oa":false,"landing_page_url":"http://irep.iium.edu.my/25593/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7095829744","https://openalex.org/W1687077942","https://openalex.org/W2148608679","https://openalex.org/W3022995359","https://openalex.org/W2040766195","https://openalex.org/W2301895154","https://openalex.org/W1974976971","https://openalex.org/W2294931306","https://openalex.org/W2033585778","https://openalex.org/W4280539585"],"abstract_inverted_index":{"One":[0],"of":[1,13,31,92,95,112,118,143,151,165,175,191,198,206,220,242,244,257,267,291,299,312],"the":[2,11,29,78,90,113,116,128,134,149,152,159,173,192,196,204,292,303,317],"most":[3,68,111],"common":[4,69],"critics":[5],"leveled":[6],"against":[7],"meta-analysis":[8,268],"pertains":[9],"to":[10,28,64,72,104,107,147,251],"issue":[12],"publication":[14,17,75,108,160],"bias.":[15,109],"A":[16],"bias":[18,41,76,161,258,301],"may":[19],"be":[20,105],"encountered":[21],"if":[22],"a":[23,96,213],"meta":[24,122,163,230,287],"analysis":[25,123,164,231],"is":[26,77,102,146],"restricted":[27],"combination":[30,266],"results":[32,59],"obtained":[33],"from":[34,215],"studies":[35,45,52,114,208,222],"which":[36,53,101],"have":[37],"been":[38],"published.":[39,66],"The":[40,67,86,140,186,289],"occur":[42],"when":[43],"unpublished":[44],"are":[46,60,232],"associated":[47,224],"with":[48,168,225],"their":[49],"outcomes,":[50],"namely,":[51],"produced":[54],"small":[55],"effects":[56,278],"or":[57,137],"negative":[58],"more":[61],"likely":[62],"not":[63],"get":[65],"method":[70,87,156],"used":[71,178],"adjust":[73],"for":[74,99,282,306,316],"Duvall":[79],"and":[80,83,154,188,203,228,236,239,254,262,285,302,309],"Tweedie\u2019s":[81],"Trim":[82,153],"Fill":[84,155],"method.":[85],"relies":[88],"on":[89,212],"scrutiny":[91],"one":[93],"side":[94],"funnel":[97],"plot":[98],"asymmetry":[100],"assumed":[103],"due":[106],"In":[110],"investigating":[115],"performance":[117],"this":[119,144,180],"method,":[120],"binary":[121],"data":[124,167,177],"were":[125,182,210,248,280,295],"used,":[126,209],"utilizing":[127],"effect":[129,293],"size":[130,197],"measures":[131],"such":[132],"as":[133,172],"odds":[135],"ratio,":[136],"risk":[138],"relative.":[139],"main":[141],"aim":[142],"study":[145,181,201],"evaluate":[148],"efficacy":[150],"in":[157,162,179,297,310],"correcting":[158],"continuous":[166],"standardized":[169],"mean":[170],"difference":[171],"measure":[174],"effects.\r\n\r\nThe":[176],"simulated":[183,193],"using":[184],"R.":[185],"characteristics":[187],"assigned":[189],"values":[190],"meta-analysis,":[194],"namely":[195],"treatment":[199],"effects,":[200],"variances":[202],"number":[205],"primary":[207,221],"based":[211],"meta-analyses":[214],"medical":[216],"research.":[217],"Three":[218],"levels":[219,241],",N,":[223],"small,":[226],"medium":[227,253],"large":[229],"N":[233],"=10,":[234],"30":[235],"50/100,":[237],"respectively,":[238],"six":[240],"percentage":[243],"missing":[245],"publications":[246],",x%,":[247],"induced,":[249],"corresponds":[250],"high,":[252],"low":[255],"degree":[256],"at":[259],"70%/50%,":[260],"30%/20%":[261],"10%/5%,":[263],"respectively.":[264],"Each":[265],"generated":[269],"was":[270],"replicated":[271],"10,000":[272],"times.":[273],"\r\n\r\nThe":[274],"inverse-variance":[275],"weighted":[276],"random":[277],"estimate":[279],"computed":[281],"both":[283],"unadjusted":[284],"adjusted":[286],"analysis.":[288],"assessment":[290],"estimates":[294],"evaluated":[296],"terms":[298,311],"statistical":[300],"standard":[304],"errors":[305],"point":[307],"estimates,":[308],"confidence":[313],"band":[314],"coverage":[315],"interval":[318],"estimates.":[319]},"counts_by_year":[],"updated_date":"2025-11-06T04:12:42.849631","created_date":"2016-06-24T00:00:00"}
