{"id":"https://openalex.org/W2001482648","doi":"https://doi.org/10.1080/00401706.1968.10490536","title":"Augmenting Existing Data in Multiple Regression","display_name":"Augmenting Existing Data in Multiple Regression","publication_year":1968,"publication_date":"1968-02-01","ids":{"openalex":"https://openalex.org/W2001482648","doi":"https://doi.org/10.1080/00401706.1968.10490536","mag":"2001482648"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.1968.10490536","doi":"https://doi.org/10.1080/00401706.1968.10490536","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.1968.10490536","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","doyens","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5113686606","display_name":"David W. Gaylor","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I180297670","display_name":"RTI International","ror":"https://ror.org/052tfza37","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I137902535","https://openalex.org/I170897317","https://openalex.org/I180297670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. W. Gaylor","raw_affiliation_strings":["Research Triangle Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Triangle Institute","institution_ids":["https://openalex.org/I180297670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035089048","display_name":"J. A. Merrill","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I180297670","display_name":"RTI International","ror":"https://ror.org/052tfza37","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I137902535","https://openalex.org/I170897317","https://openalex.org/I180297670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. A. Merrill","raw_affiliation_strings":["Research Triangle Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Triangle Institute","institution_ids":["https://openalex.org/I180297670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180297670"],"apc_list":null,"apc_paid":null,"fwci":2.5826,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.87140532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"10","issue":"1","first_page":"73","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.0017000000225380063,"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/T13141","display_name":"Statistical Methods and Applications","score":0.00019999999494757503,"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/data-augmentation","display_name":"data augmentation","score":0.7540000081062317},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.8379999995231628},{"id":"https://openalex.org/keywords/non-orthogonal-designs","display_name":"non-orthogonal designs","score":0.7680000066757202},{"id":"https://openalex.org/keywords/simultaneous-confidence-regions","display_name":"simultaneous confidence regions","score":0.7860000133514404}],"concepts":[{"id":"https://openalex.org/C27574286","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Variables","level":2,"score":0.6374773979187012},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5987377166748047},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5647502541542053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5500279664993286},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5404189229011536},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5388822555541992},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5310879945755005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3873252272605896},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00401706.1968.10490536","doi":"https://doi.org/10.1080/00401706.1968.10490536","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.1968.10490536","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","doyens","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},{"id":"doi:10.2307/1266225","doi":"https://doi.org/10.2307/1266225","is_oa":false,"landing_page_url":"https://doi.org/10.2307/1266225","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","doyens","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2021142183","https://openalex.org/W2026878869","https://openalex.org/W2085499762"],"related_works":["https://openalex.org/W2567285758","https://openalex.org/W4386077296","https://openalex.org/W2051079112","https://openalex.org/W2084253536","https://openalex.org/W2050297026","https://openalex.org/W4253987054","https://openalex.org/W999483849","https://openalex.org/W2061842808","https://openalex.org/W7098344427","https://openalex.org/W2090910911"],"abstract_inverted_index":{"Multiple":[0],"regression":[1,129],"analysis":[2],"can":[3,163,180],"be":[4,20,164,181],"used":[5],"to":[6,13,29,49,74],"analyze":[7],"data":[8,57,102,175],"from":[9],"undesigned,":[10],"non-orthogonal":[11],"experiments,":[12],"provide":[14],"a":[15,59,86,104,138,170,192],"prediction":[16],"equation":[17],"which":[18,37],"may":[19],"adequate":[21],"for":[22,33,85,100,124],"many":[23],"purposes.":[24],"However,":[25],"it":[26,45],"is":[27,46,98,113,131,144],"impossible":[28],"separate":[30],"the":[31,55,67,93,117,120,125,128,134,142,147,150,153,185,196,200],"effects":[32,162],"those":[34],"independent":[35,68,94,154],"variables":[36,69,155],"are":[38,70,156,188],"highly":[39],"correlated":[40],"with":[41,58,89,191],"each":[42,75],"other.":[43,76],"Thus,":[44],"often":[47],"desirable":[48],"augment,":[50],"in":[51,141,158,199],"an":[52],"efficient":[53],"manner,":[54],"existing":[56],"fixed":[60],"number":[61,172],"of":[62,119,127,137,173],"experimental":[63],"runs":[64],"such":[65,80,115,183],"that":[66,116,149,160,184],"made":[71],"more":[72],"orthogonal":[73],"In":[77],"this":[78],"study,":[79],"methods":[81],"have":[82],"been":[83],"developed":[84],"linear":[87],"model":[88],"no":[90],"interactions":[91],"among":[92,152],"variables.":[95],"A":[96,110],"solution":[97,112],"obtained":[99,114],"augmenting":[101],"within":[103],"region":[105,123,143],"defined":[106],"by":[107],"rectangular":[108],"limits.":[109],"theoretical":[111],"volume":[118],"simultaneous":[121],"confidence":[122],"estimates":[126],"coefficients":[130],"minimized":[132,145],"and":[133,166],"maximum":[135],"variance":[136],"predicted":[139],"response":[140],"under":[146],"restriction":[148],"correlations":[151],"eliminated,":[157],"order":[159],"their":[161],"estimated":[165],"tested":[167],"separately.":[168],"With":[169],"moderate":[171],"additional":[174],"points,":[176],"these":[177],"augmented":[178],"designs":[179],"constructed":[182],"desired":[186],"conditions":[187],"approximately":[189],"fulfilled":[190],"considerable":[193],"gain":[194],"over":[195],"information":[197],"contained":[198],"original":[201],"data.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
