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Imputing nonresponses to mail-back questionnaires.

¹Department of Epidemiology and Biostatistics, School of Public Health, University of South Carolina, Columbia 29208.

American Journal of Epidemiology

|October 15, 1991

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This study introduces a method to improve low response rates in mail-back surveys by imputing missing data. The technique uses multiple mailouts to predict and correct for non-responses, enhancing survey accuracy.

Area of Science:

Survey methodology
Statistical imputation

Background:

Mail-back surveys often suffer from low response rates, typically 15-30%.
Addressing non-response bias is crucial for survey validity.

Purpose of the Study:

To develop and validate a method for correcting poor response rates in mail-back surveys.
To impute responses for individuals who do not return questionnaires.

Main Methods:

Implementing multiple mailouts (two or three) at regular intervals.
Assuming a response trend based on the number of mailouts received.
Imputing responses for non-respondents after the final mailout.
Deriving standard errors for the imputed data.

Main Results:

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The proposed imputation method is easily programmable.
The method demonstrated effectiveness in a validation study.
The approach allows for correction of low response rates.

Conclusions:

This imputation technique offers a practical solution to enhance mail-back survey data.
The method improves the reliability of survey findings by addressing non-response bias.