{"id":"https://openalex.org/W2016405610","doi":"https://doi.org/10.1002/sim.1702","title":"Sensitivity analysis of longitudinal normal data with drop\u2010outs","display_name":"Sensitivity analysis of longitudinal normal data with drop\u2010outs","publication_year":2004,"publication_date":"2004-03-23","ids":{"openalex":"https://openalex.org/W2016405610","doi":"https://doi.org/10.1002/sim.1702","mag":"2016405610","pmid":"https://pubmed.ncbi.nlm.nih.gov/15057877"},"language":"en","primary_location":{"id":"doi:10.1002/sim.1702","doi":"https://doi.org/10.1002/sim.1702","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sim.1702","pdf_url":null,"source":{"id":"https://openalex.org/S55189604","display_name":"Statistics in Medicine","issn_l":"0277-6715","issn":["0277-6715","1097-0258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics in Medicine","raw_type":"journal-article"},"volume":null,"type":"article","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/A5112206272","display_name":"Pascal Minini","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154526488","display_name":"Inserm","ror":"https://ror.org/02vjkv261","country_code":"FR","type":"government","lineage":["https://openalex.org/I154526488"]},{"id":"https://openalex.org/I4210101023","display_name":"GlaxoSmithKline (France)","ror":"https://ror.org/00z1h3j87","country_code":"FR","type":"company","lineage":["https://openalex.org/I188950975","https://openalex.org/I4210101023"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Pascal Minini","raw_affiliation_strings":["Laboratoire GlaxoSmithKline, Unit\u00e9 M\u00e9thodologie et Biostatistique, 100 route de Versailles, 78163 Marly le Roi, France. minini@vjf.inserm.fr","INSERM U472, 16 avenue Paul Vaillant\u2010Couturier, 94807 Villejuif, France","Laboratoire GlaxoSmithKline, Unit\u00e9 M\u00e9thodologie et Biostatistique, 100 route de Versailles, 78163 Marly le Roi, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire GlaxoSmithKline, Unit\u00e9 M\u00e9thodologie et Biostatistique, 100 route de Versailles, 78163 Marly le Roi, France. minini@vjf.inserm.fr","institution_ids":["https://openalex.org/I154526488","https://openalex.org/I4210101023"]},{"raw_affiliation_string":"INSERM U472, 16 avenue Paul Vaillant\u2010Couturier, 94807 Villejuif, France","institution_ids":["https://openalex.org/I154526488"]},{"raw_affiliation_string":"Laboratoire GlaxoSmithKline, Unit\u00e9 M\u00e9thodologie et Biostatistique, 100 route de Versailles, 78163 Marly le Roi, France","institution_ids":["https://openalex.org/I4210101023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113618192","display_name":"Michel Chavance","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154526488","display_name":"Inserm","ror":"https://ror.org/02vjkv261","country_code":"FR","type":"government","lineage":["https://openalex.org/I154526488"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Michel Chavance","raw_affiliation_strings":["INSERM U472, 16 avenue Paul Vaillant-Couturier, 94807 Villejuif, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INSERM U472, 16 avenue Paul Vaillant-Couturier, 94807 Villejuif, France","institution_ids":["https://openalex.org/I154526488"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112206272"],"corresponding_institution_ids":["https://openalex.org/I154526488","https://openalex.org/I4210101023"],"apc_list":{"value":5450,"currency":"USD","value_usd":5450},"apc_paid":null,"fwci":1.6881,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8513671,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":"7","first_page":"1039","last_page":"1054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9940999746322632,"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":0.9940999746322632,"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":0.005499999970197678,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":0.0,"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/sensitivity-analysis","display_name":"sensitivity analysis","score":0.9359999895095825},{"id":"https://openalex.org/keywords/longitudinal-data","display_name":"longitudinal data","score":0.8040000200271606},{"id":"https://openalex.org/keywords/selection-model","display_name":"selection model","score":0.8519999980926514},{"id":"https://openalex.org/keywords/missing-data","display_name":"missing data","score":0.7149999737739563},{"id":"https://openalex.org/keywords/stochastic-em-algorithm","display_name":"stochastic EM algorithm","score":0.8859999775886536},{"id":"https://openalex.org/keywords/non-inferiority","display_name":"non-inferiority","score":0.7590000033378601},{"id":"https://openalex.org/keywords/inhaled-corticosteroids","display_name":"inhaled corticosteroids","score":0.8740000128746033},{"id":"https://openalex.org/keywords/bone-mineral-density","display_name":"bone mineral density","score":0.9779999852180481},{"id":"https://openalex.org/keywords/randomized-controlled-trials","display_name":"randomized controlled trials","score":0.6629999876022339}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6047789454460144},{"id":"https://openalex.org/C2984949393","wikidata":"https://www.wikidata.org/wiki/Q1260241","display_name":"Drop out","level":2,"score":0.5704928040504456},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5537421703338623},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.5202480554580688},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.5118550658226013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49609145522117615},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4647834300994873},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3382555842399597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08668261766433716},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C4249254","wikidata":"https://www.wikidata.org/wiki/Q3044431","display_name":"Demographic economics","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000068298","descriptor_name":"Fluticasone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000293","descriptor_name":"Adolescent","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000730","descriptor_name":"Androstadienes","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false},{"descriptor_ui":"D001249","descriptor_name":"Asthma","qualifier_ui":"Q000188","qualifier_name":"drug therapy","is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D008137","descriptor_name":"Longitudinal Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010352","descriptor_name":"Patient Dropouts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015519","descriptor_name":"Bone Density","qualifier_ui":"Q000187","qualifier_name":"drug effects","is_major_topic":false},{"descriptor_ui":"D016032","descriptor_name":"Randomized Controlled Trials as Topic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017835","descriptor_name":"Nedocromil","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false},{"descriptor_ui":"D018927","descriptor_name":"Anti-Asthmatic Agents","qualifier_ui":"Q000627","qualifier_name":"therapeutic use","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1002/sim.1702","doi":"https://doi.org/10.1002/sim.1702","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sim.1702","pdf_url":null,"source":{"id":"https://openalex.org/S55189604","display_name":"Statistics in Medicine","issn_l":"0277-6715","issn":["0277-6715","1097-0258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics in Medicine","raw_type":"journal-article"},{"id":"pmid:15057877","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/15057877","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":"Statistics in medicine","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7246000170707703,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320307773","display_name":"GlaxoSmithKline","ror":"https://ror.org/01xsqw823"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W935860710","https://openalex.org/W1550443206","https://openalex.org/W1591638896","https://openalex.org/W1592576206","https://openalex.org/W1990139173","https://openalex.org/W1991567646","https://openalex.org/W2009386843","https://openalex.org/W2010670304","https://openalex.org/W2020858487","https://openalex.org/W2024291119","https://openalex.org/W2037049254","https://openalex.org/W2043805511","https://openalex.org/W2044758663","https://openalex.org/W2044814316","https://openalex.org/W2050762021","https://openalex.org/W2065515505","https://openalex.org/W2069091142","https://openalex.org/W2097147565","https://openalex.org/W2111636520","https://openalex.org/W2118502261","https://openalex.org/W2139972977","https://openalex.org/W2145816995","https://openalex.org/W2158197616","https://openalex.org/W2163387675","https://openalex.org/W2313407065","https://openalex.org/W2461735667","https://openalex.org/W4230076583","https://openalex.org/W4231308716","https://openalex.org/W4300187280","https://openalex.org/W4388319941"],"related_works":["https://openalex.org/W2049380844","https://openalex.org/W2954256999","https://openalex.org/W1974193951","https://openalex.org/W2515838309","https://openalex.org/W4389056514","https://openalex.org/W6999491642","https://openalex.org/W1967740493","https://openalex.org/W2912153926","https://openalex.org/W2020858487","https://openalex.org/W1979616383"],"abstract_inverted_index":{"We":[0],"propose":[1],"to":[2,7,11,39,48,55,88,120,141,147],"perform":[3],"a":[4,15,29,49,82,142,161],"sensitivity":[5],"analysis":[6,165],"evaluate":[8,56],"the":[9,33,36,40,60,65,76,97,106,128,168,178],"extent":[10],"which":[12],"results":[13],"from":[14],"longitudinal":[16],"study":[17],"can":[18],"be":[19],"affected":[20],"by":[21],"informative":[22],"drop-outs.":[23],"The":[24],"method":[25,138],"is":[26,43,86,100],"based":[27],"on":[28,75],"selection":[30],"model,":[31],"where":[32],"parameter":[34,99,130],"relating":[35],"dropout":[37],"probability":[38],"current":[41],"observation":[42],"not":[44,132],"estimated,":[45],"but":[46],"fixed":[47],"set":[50],"of":[51,62,64,71,105,114,127,150,156,170],"values.":[52],"This":[53,137],"allows":[54],"several":[57],"hypotheses":[58,176],"for":[59,177],"degree":[61],"informativeness":[63],"drop-out":[66,77,98,129,179],"process.":[67,180],"Expectation":[68],"and":[69,81,111],"variance":[70],"missing":[72],"data,":[73],"conditional":[74],"time":[78],"are":[79,109,118],"computed,":[80],"stochastic":[83],"EM":[84],"algorithm":[85],"used":[87],"obtain":[89],"maximum":[90],"likelihood":[91],"estimates.":[92],"Simulations":[93],"show":[94],"that":[95,167],"when":[96],"correctly":[101],"specified,":[102],"unbiased":[103],"estimates":[104],"other":[107],"parameters":[108],"obtained,":[110],"coverage":[112],"percentages":[113],"their":[115,121],"confidence":[116],"intervals":[117],"close":[119],"theoretical":[122],"value.":[123],"More":[124],"interestingly,":[125],"misspecification":[126],"does":[131],"considerably":[133],"alter":[134],"these":[135],"results.":[136],"was":[139,172],"applied":[140],"randomized":[143],"clinical":[144],"trial,":[145],"designed":[146],"demonstrate":[148],"non-inferiority":[149,171],"an":[151],"inhaled":[152],"corticosteroid":[153],"in":[154],"terms":[155],"bone":[157],"density,":[158],"compared":[159],"with":[160],"reference":[162],"treatment.":[163],"Sensitivity":[164],"showed":[166],"conclusion":[169],"robust":[173],"against":[174],"different":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2016-06-24T00:00:00"}