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Response and Nonresponse Bias in Oral Health Surveys
Author(s) -
Locker David
Publication year - 2000
Publication title -
journal of public health dentistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 63
eISSN - 1752-7325
pISSN - 0022-4006
DOI - 10.1111/j.1752-7325.2000.tb03298.x
Subject(s) - non response bias , imputation (statistics) , statistics , weighting , sample (material) , data collection , data quality , sample size determination , missing data , sampling bias , population , sampling (signal processing) , response bias , medicine , econometrics , computer science , environmental health , mathematics , metric (unit) , chemistry , operations management , filter (signal processing) , chromatography , economics , computer vision , radiology
Oral health surveys are undertaken to provide estimates of the dental health and behaviors of populations or population subgroups. However, the integrity of the data from sample surveys may be compromised by one or more sources of sampling and nonsampling error. An important source of nonsampling error is the failure to collect data from some of the individuals comprising the sample. Consequently, the response to a sample survey, and the direction and magnitude of bias induced by nonresponse, need to be taken into account when using estimates derived from sample surveys. Although the response rate to a survey is usually used as an indicator of the quality of the data it provides, nonresponse error is a function of nonresponse and the extent of differences in the characteristics of responders and nonresponders. Nonresponse may be managed in two ways. The first is to reduce nonresponse to a minimum using response‐enhancement strategies. The second is the post‐survey adjustment of data using weighting or imputation techniques to produce estimates that correct for nonresponse. This paper discusses issues concerning response and nonresponse bias in oral health surveys and provides guidelines on the management and reporting of nonresponse. It describes response‐enhancement strategies to reduce noncontacts and refusals, sources of data to facilitate the comparison of responders and nonresponders, methods of assessing the degree of bias induced by nonresponse, techniques for producing adjusted survey estimates, and the assumptions on which these procedures and processes are based.