Nonresponse and recall errors in a study of absence because of illness: An analysis of their effects on distributions and relationships

Abstract

Using administrative data as validating standard, we studied the combined effects of two sources of survey error - nonresponse and recall errors - on distributional and substantive bias in a mail survey of absence because of illness among the employees of a Dutch road building company (response rate 77%). No distributional bias was found in five socio-demographic variables (sex, age, years of service, function, and district), but both nonresponse bias and recall bias occurred in our central dependent variables: frequency and duration of absence because of illness. Nonrespondents were on sick leave more frequently and longer than respondents. Furthermore, the self-reports of absence because of illness of our respondents proved to be rather inaccurate. Underreporting of frequency and duration of sick leave was more common than overreporting. Therefore, both sources of error had a cumulative effect. While nonresponse did not result in biased relationships, recall errors had clearly biasing consequences: seven out of 30 correlation coefficients analyzed were too biased to produce valid outcomes; another six were substantially biased. Multiple regression used for predicting recent absence because of illness among our respondents also led to different outcomes depending on the choice of data source (administration or questionnaire) for our absence variables.