{"id":"https://openalex.org/W1604779258","doi":null,"title":"Statistical methods for missing data in complex sample surveys.","display_name":"Statistical methods for missing data in complex sample surveys.","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W1604779258","mag":"1604779258"},"language":"en","primary_location":{"id":"mag:1604779258","doi":null,"is_oa":false,"landing_page_url":"https://deepblue.lib.umich.edu/bitstream/handle/2027.42/63657/fedarko_1.pdf;sequence=1","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":"book","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/A5072262441","display_name":"Roderick J. A. Little","orcid":"https://orcid.org/0000-0001-9878-6977","observed_orcids":["https://orcid.org/0000-0001-9878-6977"]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roderick J. A. Little","raw_affiliation_strings":["(University of Michigan)"],"raw_orcid":"https://orcid.org/0000-0001-9878-6977","affiliations":[{"raw_affiliation_string":"(University of Michigan)","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040135295","display_name":"Rebecca Andridge","orcid":"https://orcid.org/0000-0001-9991-9647","observed_orcids":["https://orcid.org/0000-0001-9991-9647"]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rebecca Andridge","raw_affiliation_strings":["(University of Michigan)"],"raw_orcid":"https://orcid.org/0000-0001-9991-9647","affiliations":[{"raw_affiliation_string":"(University of Michigan)","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"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/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.8529999852180481,"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/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.8529999852180481,"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/T11539","display_name":"Survey Methodology and Nonresponse","score":0.11840000003576279,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.023900000378489494,"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":0.8619999885559082},{"id":"https://openalex.org/keywords/survey-nonresponse","display_name":"survey nonresponse","score":0.9559999704360962},{"id":"https://openalex.org/keywords/hot-deck-imputation","display_name":"hot deck imputation","score":0.9810000061988831},{"id":"https://openalex.org/keywords/nonresponse-bias","display_name":"nonresponse bias","score":0.9010000228881836},{"id":"https://openalex.org/keywords/sampling-weights","display_name":"sampling weights","score":0.8759999871253967},{"id":"https://openalex.org/keywords/missing-at-random","display_name":"missing at random","score":0.8740000128746033},{"id":"https://openalex.org/keywords/missing-not-at-random","display_name":"missing not at random","score":0.8500000238418579},{"id":"https://openalex.org/keywords/auxiliary-information","display_name":"auxiliary information","score":0.7689999938011169},{"id":"https://openalex.org/keywords/probit-analysis","display_name":"probit model","score":0.8119999766349792},{"id":"https://openalex.org/keywords/model-misspecification","display_name":"model misspecification","score":0.8960000276565552},{"id":"https://openalex.org/keywords/nhanes-iii","display_name":"NHANES III","score":0.7789999842643738}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8840240240097046},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.8667134046554565},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5410385131835938},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.5197881460189819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4868713915348053},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.47147443890571594},{"id":"https://openalex.org/C40423286","wikidata":"https://www.wikidata.org/wiki/Q284172","display_name":"Selection bias","level":2,"score":0.46091631054878235},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.42817923426628113},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3928382992744446},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2519853413105011},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:1604779258","doi":null,"is_oa":false,"landing_page_url":"https://deepblue.lib.umich.edu/bitstream/handle/2027.42/63657/fedarko_1.pdf;sequence=1","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":77,"referenced_works":["https://openalex.org/W107734494","https://openalex.org/W131600860","https://openalex.org/W166843393","https://openalex.org/W175148995","https://openalex.org/W216715903","https://openalex.org/W289190035","https://openalex.org/W1536282935","https://openalex.org/W1573084488","https://openalex.org/W1591638896","https://openalex.org/W1592576206","https://openalex.org/W1606533552","https://openalex.org/W1918432791","https://openalex.org/W1949002577","https://openalex.org/W1960964799","https://openalex.org/W1965268674","https://openalex.org/W1972851018","https://openalex.org/W1973907010","https://openalex.org/W1977845116","https://openalex.org/W1981987056","https://openalex.org/W1983724935","https://openalex.org/W1986056512","https://openalex.org/W1986837204","https://openalex.org/W1989279378","https://openalex.org/W1989972396","https://openalex.org/W1990487119","https://openalex.org/W1993725629","https://openalex.org/W1999508687","https://openalex.org/W2001768898","https://openalex.org/W2001994823","https://openalex.org/W2002374079","https://openalex.org/W2005482719","https://openalex.org/W2009763213","https://openalex.org/W2019045453","https://openalex.org/W2021746604","https://openalex.org/W2026525327","https://openalex.org/W2031475824","https://openalex.org/W2032594557","https://openalex.org/W2037049254","https://openalex.org/W2038637022","https://openalex.org/W2042934584","https://openalex.org/W2044758663","https://openalex.org/W2047391263","https://openalex.org/W2052254591","https://openalex.org/W2059820613","https://openalex.org/W2063109494","https://openalex.org/W2066583279","https://openalex.org/W2072727561","https://openalex.org/W2073031042","https://openalex.org/W2083528721","https://openalex.org/W2083653302","https://openalex.org/W2086591490","https://openalex.org/W2086604918","https://openalex.org/W2108306139","https://openalex.org/W2109391176","https://openalex.org/W2109927751","https://openalex.org/W2116971494","https://openalex.org/W2118502261","https://openalex.org/W2125884535","https://openalex.org/W2127053344","https://openalex.org/W2133470535","https://openalex.org/W2133478656","https://openalex.org/W2139972977","https://openalex.org/W2153476503","https://openalex.org/W2154529659","https://openalex.org/W2156910914","https://openalex.org/W2164422502","https://openalex.org/W2185079239","https://openalex.org/W2189296673","https://openalex.org/W2321237259","https://openalex.org/W2327235407","https://openalex.org/W2339915790","https://openalex.org/W2599222635","https://openalex.org/W2980351783","https://openalex.org/W3085162807","https://openalex.org/W3122541118","https://openalex.org/W3166877753","https://openalex.org/W4211101039"],"related_works":["https://openalex.org/W175148995","https://openalex.org/W131600860","https://openalex.org/W2162313689","https://openalex.org/W2032627149","https://openalex.org/W3161174373","https://openalex.org/W2241231910","https://openalex.org/W2187121961","https://openalex.org/W2185079239","https://openalex.org/W4399511805","https://openalex.org/W7097921243"],"abstract_inverted_index":{"Missing":[0],"data":[1,203,334],"are":[2,327],"a":[3,11,18,224,247,258,284,289],"pervasive":[4],"problem":[5],"in":[6,32,57,79,97,109,123,193,204],"large-scale":[7],"surveys,":[8],"arising":[9],"when":[10,167,232,262],"sampled":[12],"unit":[13],"does":[14],"not":[15,63,163,235],"respond":[16],"to":[17,22,105,172,185,287,305,333],"particular":[19],"question":[20],"or":[21],"the":[23,75,83,86,92,98,117,139,168,173,177,191,205,217,273,303,315,324],"entire":[24],"survey.":[25],"This":[26],"dissertation":[27],"addresses":[28,91],"two":[29,219],"major":[30],"topics":[31],"survey":[33,260],"nonresponse:":[34],"hot":[35,49,99,160],"deck":[36,50],"imputation":[37,71],"and":[38,149,176,180,228,252,282,307,331],"evaluation":[39],"of":[40,48,69,74,94,111,121,141,291,302,318],"nonresponse":[41,230,255],"bias.Chapter":[42],"II":[43],"contains":[44],"an":[45,124,182,300],"extensive":[46],"review":[47,81],"imputation,":[51],"which":[52,114],"despite":[53],"being":[54],"used":[55],"extensively":[56],"practice":[58],"has":[59],"theory":[60],"that":[61,68,135,157,188],"is":[62,82,104,170,211,264,321],"as":[64,67],"well":[65],"developed":[66],"other":[70],"methods.":[72],"One":[73],"understudied":[76],"areas":[77],"discovered":[78],"this":[80,153],"topic":[84],"for":[85,143,165,200,226,250,254,257],"subsequent":[87],"chapter:":[88],"Chapter":[89,240,296],"III":[90],"use":[93],"sample":[95,107,119],"weights":[96,108,137],"deck.":[100],"The":[101],"naive":[102],"approach":[103],"ignore":[106],"creation":[110],"adjustment":[112,125],"cells,":[113],"effectively":[115],"imputes":[116],"unweighted":[118],"distribution":[120],"respondents":[122],"cell,":[126],"potentially":[127],"causing":[128],"bias.":[129],"Alternative":[130],"approaches":[131],"have":[132],"been":[133],"proposed":[134],"incorporate":[136],"into":[138],"probabilities":[140],"selection":[142],"each":[144],"donor":[145],"(Cox,":[146],"1980;":[147],"Rao":[148],"Shao,":[150],"1992).":[151],"In":[152,295,313],"chapter":[154],"we":[155,298],"show":[156],"these":[158,194],"weighted":[159],"decks":[161],"do":[162],"correct":[164,190],"bias":[166,192,231,256],"outcome":[169,261],"related":[171],"sampling":[174],"weight":[175],"response":[178],"propensity,":[179],"suggest":[181],"alternative,":[183],"simple":[184],"implement":[186],"method":[187,225,249],"can":[189],"situations.The":[195],"first":[196],"chapters":[197,220],"concern":[198],"methods":[199,326],"imputing":[201],"missing":[202],"case":[206],"where":[207],"(at":[208],"worst)":[209],"missingness":[210,233,293],"at":[212,237],"random":[213,238],"(MAR)":[214],"(Rubin,":[215],"1976);":[216],"final":[218],"focus":[221],"instead":[222],"on":[223],"estimating":[227],"correcting":[229],"may":[234],"be":[236],"(NMAR).":[239],"IV":[241],"introduces":[242],"proxy":[243],"pattern-mixture":[244],"analysis":[245,286],"(PPMA),":[246],"new":[248],"assessing":[251],"adjusting":[253],"continuous":[259],"there":[263],"some":[265],"fully":[266],"observed":[267],"auxiliary":[268],"information":[269],"available.":[270],"We":[271],"describe":[272],"PPMA":[274,304],"model":[275,319],"along":[276],"with":[277],"several":[278],"different":[279],"estimation":[280],"strategies":[281],"propose":[283,299],"sensitivity":[285],"capture":[288],"range":[290],"potential":[292],"mechanisms.":[294],"V":[297],"extension":[301],"binary":[306],"ordinal":[308],"outcomes":[309],"using":[310],"probit":[311],"models.":[312],"addition,":[314],"important":[316],"issue":[317],"misspecification":[320],"discussed.":[322],"Throughout":[323],"dissertation,":[325],"illustrated":[328],"through":[329],"simulation":[330],"application":[332],"from":[335],"NHANES":[336],"III.":[337]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2016-06-24T00:00:00"}