{"id":"https://openalex.org/W2930957652","doi":"https://doi.org/10.1080/03610918.2019.1588308","title":"Small area estimation combining data from two surveys","display_name":"Small area estimation combining data from two surveys","publication_year":2019,"publication_date":"2019-04-03","ids":{"openalex":"https://openalex.org/W2930957652","doi":"https://doi.org/10.1080/03610918.2019.1588308","mag":"2930957652"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1588308","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1588308","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/A5043236544","display_name":"Sadikul Islam","orcid":null},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sadikul Islam","raw_affiliation_strings":["ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035821671","display_name":"Hukum Chandra","orcid":"https://orcid.org/0000-0002-8502-7354"},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Hukum Chandra","raw_affiliation_strings":["ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5035821671"],"corresponding_institution_ids":["https://openalex.org/I1141210"],"apc_list":null,"apc_paid":null,"fwci":0.4408,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.60356667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9570000171661377,"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/T12773","display_name":"Water Quality and Resources Studies","score":0.9390000104904175,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/small-area-estimation","display_name":"Small area estimation","score":0.7459317445755005},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5877395272254944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42505279183387756},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40848782658576965},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.32630646228790283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21924588084220886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12509390711784363},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.05801478028297424}],"concepts":[{"id":"https://openalex.org/C129963666","wikidata":"https://www.wikidata.org/wiki/Q17105857","display_name":"Small area estimation","level":3,"score":0.7459317445755005},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5877395272254944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42505279183387756},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40848782658576965},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.32630646228790283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21924588084220886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12509390711784363},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.05801478028297424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1588308","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1588308","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":28,"referenced_works":["https://openalex.org/W178764966","https://openalex.org/W1644332301","https://openalex.org/W1906190121","https://openalex.org/W1973422203","https://openalex.org/W1976239071","https://openalex.org/W1978645190","https://openalex.org/W1982585616","https://openalex.org/W1996549107","https://openalex.org/W2009378006","https://openalex.org/W2009877219","https://openalex.org/W2029555586","https://openalex.org/W2029685080","https://openalex.org/W2060521676","https://openalex.org/W2061458074","https://openalex.org/W2075849865","https://openalex.org/W2092407310","https://openalex.org/W2097188985","https://openalex.org/W2106230029","https://openalex.org/W2141390646","https://openalex.org/W2146492601","https://openalex.org/W2188823313","https://openalex.org/W2254396509","https://openalex.org/W2255868970","https://openalex.org/W2489398676","https://openalex.org/W2507058334","https://openalex.org/W2747984756","https://openalex.org/W4229671821","https://openalex.org/W4254103647"],"related_works":["https://openalex.org/W309072737","https://openalex.org/W2896041930","https://openalex.org/W2183433221","https://openalex.org/W1985711056","https://openalex.org/W2893031534","https://openalex.org/W2065867141","https://openalex.org/W2727685709","https://openalex.org/W2936000918","https://openalex.org/W2321362088","https://openalex.org/W1870121983"],"abstract_inverted_index":{"Many":[0],"often":[1],"two":[2,66,83],"surveys":[3,84],"conducted":[4],"independently":[5],"with":[6],"same":[7],"or":[8],"different":[9],"objectives,":[10],"may":[11],"have":[12],"some":[13,46],"auxiliary":[14,34,47],"variables":[15,48],"in":[16,41,49],"common.":[17],"The":[18,36],"first":[19,53],"survey,":[20,38],"which":[21],"has":[22,44],"small":[23,56,74],"sample":[24,42],"size,":[25,43],"collects":[26],"both":[27],"variable":[28],"of":[29],"interest":[30],"as":[31,33],"well":[32],"variables.":[35],"second":[37],"relatively":[39],"larger":[40],"only":[45],"common":[50],"to":[51,79],"the":[52,72],"survey.":[54],"A":[55],"area":[57,75],"predictor":[58,76],"is":[59],"proposed":[60,73],"by":[61],"combining":[62],"data":[63],"from":[64],"these":[65],"surveys.":[67],"Empirical":[68],"results":[69],"show":[70],"that":[71],"can":[77],"lead":[78],"efficiency":[80],"gains":[81],"when":[82],"are":[85],"combined.":[86]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
