{"id":"https://openalex.org/W2942382682","doi":"https://doi.org/10.1080/03610918.2019.1601215","title":"Analysis of mixed longitudinal (<i>k</i>,<i>l</i>)-Inflated power series, ordinal and continuous responses with sensitivity analysis to non-ignorable missing mechanism","display_name":"Analysis of mixed longitudinal (<i>k</i>,<i>l</i>)-Inflated power series, ordinal and continuous responses with sensitivity analysis to non-ignorable missing mechanism","publication_year":2019,"publication_date":"2019-04-22","ids":{"openalex":"https://openalex.org/W2942382682","doi":"https://doi.org/10.1080/03610918.2019.1601215","mag":"2942382682"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1601215","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1601215","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/A5022950845","display_name":"F. Razie","orcid":null},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Farzaneh Razie","raw_affiliation_strings":["Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046239754","display_name":"Ehsan Bahrami Samani","orcid":"https://orcid.org/0000-0002-6726-6335"},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ehsan Bahrami Samani","raw_affiliation_strings":["Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026928158","display_name":"Mojtaba Ganjali","orcid":"https://orcid.org/0000-0002-8574-1750"},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mojtaba Ganjali","raw_affiliation_strings":["Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046239754"],"corresponding_institution_ids":["https://openalex.org/I48379061"],"apc_list":null,"apc_paid":null,"fwci":0.2341,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54676344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"50","issue":"8","first_page":"2286","last_page":"2312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9858999848365784,"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/missing-data","display_name":"Missing data","score":0.7759249806404114},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6205917596817017},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.5920904278755188},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.5469532012939453},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.546563982963562},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.513093113899231},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5122162699699402},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4965093731880188},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.4651993215084076},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4395962953567505},{"id":"https://openalex.org/keywords/mixed-model","display_name":"Mixed model","score":0.4356733560562134},{"id":"https://openalex.org/keywords/random-effects-model","display_name":"Random effects model","score":0.4214457869529724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2466244101524353}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7759249806404114},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6205917596817017},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.5920904278755188},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.5469532012939453},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.546563982963562},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.513093113899231},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5122162699699402},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4965093731880188},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.4651993215084076},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4395962953567505},{"id":"https://openalex.org/C16012445","wikidata":"https://www.wikidata.org/wiki/Q1501135","display_name":"Mixed model","level":2,"score":0.4356733560562134},{"id":"https://openalex.org/C168743327","wikidata":"https://www.wikidata.org/wiki/Q1826427","display_name":"Random effects model","level":3,"score":0.4214457869529724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2466244101524353},{"id":"https://openalex.org/C95190672","wikidata":"https://www.wikidata.org/wiki/Q815382","display_name":"Meta-analysis","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","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},{"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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1601215","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1601215","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1967740493","https://openalex.org/W1973991899","https://openalex.org/W1978227930","https://openalex.org/W1979627248","https://openalex.org/W1989670556","https://openalex.org/W1993725629","https://openalex.org/W2004887252","https://openalex.org/W2009060438","https://openalex.org/W2020858487","https://openalex.org/W2038176697","https://openalex.org/W2045084661","https://openalex.org/W2049910836","https://openalex.org/W2050207700","https://openalex.org/W2052388553","https://openalex.org/W2076983043","https://openalex.org/W2077724217","https://openalex.org/W2101856711","https://openalex.org/W2102183027","https://openalex.org/W2102810005","https://openalex.org/W2119634512","https://openalex.org/W2150983145","https://openalex.org/W2155220505","https://openalex.org/W2330330903","https://openalex.org/W2340285424","https://openalex.org/W2351767899","https://openalex.org/W2478445791","https://openalex.org/W2480680997","https://openalex.org/W2502655619","https://openalex.org/W4238306122"],"related_works":["https://openalex.org/W2599805416","https://openalex.org/W3210390693","https://openalex.org/W4214644238","https://openalex.org/W2556931687","https://openalex.org/W3135460725","https://openalex.org/W2338849605","https://openalex.org/W3122903216","https://openalex.org/W2971731486","https://openalex.org/W2095810391","https://openalex.org/W3092126196"],"abstract_inverted_index":{"Authors":[0],"propose":[1],"a":[2,95,143],"joint":[3],"random":[4,41],"effect":[5,42],"model":[6,80],"for":[7,37,127],"analyzing":[8],"longitudinal":[9,59],"mixed":[10,53],"count,":[11],"ordinal":[12],"and":[13,26,28,55,132],"continuous":[14],"responses,":[15],"where":[16],"the":[17,31,50,56,69,72,75,78,84,88,92,106,109,114],"count":[18,128],"response":[19,129],"is":[20,30,44,123,147],"inflated":[21],"in":[22,113,125],"two":[23],"points":[24],"(k":[25],"l)":[27],"there":[29],"possibility":[32],"of":[33,49,58,71,77,98,108,111],"non-ignorable":[34],"missing":[35,89,115],"values":[36],"all":[38],"responses.":[39],"The":[40,61],"approach":[43],"used":[45,65],"to":[46,66,100,104],"investigate":[47],"both":[48],"correlation":[51,57],"between":[52],"responses":[54],"nature.":[60],"likelihood-based":[62],"methods":[63],"are":[64,137],"inference":[67],"about":[68],"parameters":[70,110],"model.":[73],"However,":[74],"interpretation":[76],"fitted":[79],"highly":[81],"depends":[82],"on":[83,87,117],"assumptions":[85],"imposed":[86],"mechanism,":[90],"so":[91],"authors":[93],"extend":[94],"general":[96],"index":[97],"sensitivity":[99],"non-ignorability":[101,112],"(ISNI)":[102],"methodology":[103],"assess":[105],"impact":[107],"mechanisms":[116],"key":[118],"inferences.":[119],"A":[120],"simulation":[121],"study":[122],"performed":[124],"which":[126],"(k,l)-inflated":[130,133],"Poisson":[131],"negative":[134],"binomial":[135],"distributions":[136],"considered.":[138],"Also,":[139],"an":[140],"application":[141],"using":[142],"clinical":[144],"data":[145],"set":[146],"discussed.":[148]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
