{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Elliott MR"],"funding":["NIA NIH HHS"],"pagination":["25-48"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9983757"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["48(1)"],"pubmed_abstract":["Methodological studies of the effects that human interviewers have on the quality of survey data have long been limited by a critical assumption: that interviewers in a given survey are assigned random subsets of the larger overall sample (also known as interpenetrated assignment). Absent this type of study design, estimates of interviewer effects on survey measures of interest may reflect differences between interviewers in the characteristics of their assigned sample members, rather than recruitment or measurement effects specifically introduced by the interviewers. Previous attempts to approximate interpenetrated assignment have typically used regression models to condition on factors that might be related to interviewer assignment. We introduce a new approach for overcoming this lack o"],"journal":["Survey methodology"],"pubmed_title":["The anchoring method: Estimation of interviewer effects in the absence of interpenetrated sample assignment."],"pmcid":["PMC9983757"],"funding_grant_id":["R01 AG058599"],"pubmed_authors":["West BT","Elliott MR","Zhang X","Coffey S"],"additional_accession":[]},"is_claimable":false,"name":"The anchoring method: Estimation of interviewer effects in the absence of interpenetrated sample assignment.","description":"Methodological studies of the effects that human interviewers have on the quality of survey data have long been limited by a critical assumption: that interviewers in a given survey are assigned random subsets of the larger overall sample (also known as interpenetrated assignment). Absent this type of study design, estimates of interviewer effects on survey measures of interest may reflect differences between interviewers in the characteristics of their assigned sample members, rather than recruitment or measurement effects specifically introduced by the interviewers. Previous attempts to approximate interpenetrated assignment have typically used regression models to condition on factors that might be related to interviewer assignment. We introduce a new approach for overcoming this lack o","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Jun","modification":"2025-04-22T09:56:55.317Z","creation":"2025-04-05T23:17:15.778Z"},"accession":"S-EPMC9983757","cross_references":{"pubmed":["36873727"]}}