{"id":"https://openalex.org/W7124725648","doi":"https://doi.org/10.3390/e28010116","title":"Peer Reporting: Sampling Design and Unbiased Estimates","display_name":"Peer Reporting: Sampling Design and Unbiased Estimates","publication_year":2026,"publication_date":"2026-01-18","ids":{"openalex":"https://openalex.org/W7124725648","doi":"https://doi.org/10.3390/e28010116","pmid":"https://pubmed.ncbi.nlm.nih.gov/41594023"},"language":"en","primary_location":{"id":"doi:10.3390/e28010116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28010116","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/e28010116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116937958","display_name":"Kang Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Wen","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha 410073, China"],"raw_orcid":"https://orcid.org/0009-0002-2719-4557","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014625582","display_name":"Jianhong Mou","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhong Mou","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha 410073, China"],"raw_orcid":"https://orcid.org/0009-0001-6654-7741","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha 410073, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123295363","display_name":"Xin Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Lu","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha 410073, China"],"raw_orcid":"https://orcid.org/0000-0002-3547-6493","affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha 410073, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5123295363"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06502326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"1","first_page":"116","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.16210000216960907,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.16210000216960907,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.15919999778270721,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.1559000015258789,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7376999855041504},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5478000044822693},{"id":"https://openalex.org/keywords/bias-of-an-estimator","display_name":"Bias of an estimator","score":0.5295000076293945},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5078999996185303},{"id":"https://openalex.org/keywords/steins-unbiased-risk-estimate","display_name":"Stein's unbiased risk estimate","score":0.4675999879837036},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4442000091075897},{"id":"https://openalex.org/keywords/uncorrelated","display_name":"Uncorrelated","score":0.4171999990940094},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.40470001101493835},{"id":"https://openalex.org/keywords/reciprocity","display_name":"Reciprocity (cultural anthropology)","score":0.4034999907016754}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7376999855041504},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5478000044822693},{"id":"https://openalex.org/C191393472","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Bias of an estimator","level":4,"score":0.5295000076293945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5230000019073486},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5078999996185303},{"id":"https://openalex.org/C134962040","wikidata":"https://www.wikidata.org/wiki/Q7606742","display_name":"Stein's unbiased risk estimate","level":5,"score":0.4675999879837036},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4625000059604645},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4442000091075897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43130001425743103},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4235999882221222},{"id":"https://openalex.org/C169345407","wikidata":"https://www.wikidata.org/wiki/Q8216221","display_name":"Uncorrelated","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40950000286102295},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C169903001","wikidata":"https://www.wikidata.org/wiki/Q3264987","display_name":"Reciprocity (cultural anthropology)","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C2909318450","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Unbiased Estimation","level":3,"score":0.39899998903274536},{"id":"https://openalex.org/C35594927","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficient estimator","level":4,"score":0.3653999865055084},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C103545067","wikidata":"https://www.wikidata.org/wiki/Q796265","display_name":"Best linear unbiased prediction","level":3,"score":0.3441999852657318},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C164172150","wikidata":"https://www.wikidata.org/wiki/Q1782585","display_name":"Consistent estimator","level":4,"score":0.326200008392334},{"id":"https://openalex.org/C75373757","wikidata":"https://www.wikidata.org/wiki/Q7410160","display_name":"Sampling design","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C158587675","wikidata":"https://www.wikidata.org/wiki/Q17160413","display_name":"Mutually unbiased bases","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.2736000120639801},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C196323059","wikidata":"https://www.wikidata.org/wiki/Q7862949","display_name":"U-statistic","level":4,"score":0.26980000734329224},{"id":"https://openalex.org/C2993060064","wikidata":"https://www.wikidata.org/wiki/Q49918","display_name":"Population mean","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e28010116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28010116","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:41594023","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41594023","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,"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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a66cc7a637824b7c9899a3a2cc9147af","is_oa":true,"landing_page_url":"https://doaj.org/article/a66cc7a637824b7c9899a3a2cc9147af","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 28, Iss 1, p 116 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12840051","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12840051/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e28010116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28010116","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4817552864551544}],"awards":[{"id":"https://openalex.org/G1680205229","display_name":null,"funder_award_id":"72025405, 72421002, 92467302, 72474223, 72301285","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Ego-Centric":[1],"Sampling":[2],"Method":[3],"(ECM)":[4],"leverages":[5],"individual-level":[6],"reports":[7],"about":[8],"peers":[9],"to":[10,68,117],"estimate":[11],"population":[12],"proportions":[13],"within":[14],"social":[15],"networks,":[16],"offering":[17],"strong":[18],"privacy":[19],"protection":[20],"without":[21],"requiring":[22],"full":[23],"network":[24,66],"data.":[25],"However,":[26],"the":[27,35,57,70,121],"conventional":[28,122],"ECM":[29,61],"estimator":[30,62],"is":[31],"unbiased":[32,94,135],"only":[33],"under":[34],"restrictive":[36],"assumption":[37],"of":[38],"a":[39,127],"homogeneous":[40],"network,":[41],"where":[42],"node":[43],"degrees":[44],"are":[45],"uniform":[46],"and":[47,87,95,104,130],"uncorrelated":[48],"with":[49,120],"attributes.":[50],"To":[51],"overcome":[52],"this":[53],"limitation,":[54],"we":[55],"introduce":[56],"Activity":[58],"Ratio":[59],"Corrected":[60],"(ECMac),":[63],"which":[64],"exploits":[65],"reciprocity":[67],"recast":[69],"population-proportion":[71],"problem":[72],"into":[73],"an":[74],"equivalent":[75],"formulation":[76],"in":[77,99,137],"edge":[78],"space.":[79],"This":[80],"reformulation":[81],"relies":[82],"solely":[83],"on":[84,106],"ego-peer":[85],"data":[86],"explicitly":[88],"corrects":[89],"for":[90,134],"degree-attribute":[91],"dependencies,":[92],"yielding":[93],"stable":[96],"estimates":[97],"even":[98],"highly":[100],"heterogeneous":[101],"networks.":[102],"Simulations":[103],"analyses":[105],"real-world":[107],"networks":[108],"show":[109],"that":[110],"ECMac":[111],"reduces":[112],"estimation":[113],"error":[114],"by":[115],"up":[116],"70%":[118],"compared":[119],"ECM.":[123],"Our":[124],"results":[125],"establish":[126],"theoretically":[128],"grounded":[129],"practically":[131],"scalable":[132],"framework":[133],"inference":[136],"network-based":[138],"sampling":[139],"designs.":[140]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-20T00:00:00"}
