Skip to main content
Log in

Nonresponse and Recall Errors in a Study of Absence because of Illness: An Analysis of Their Effects on Distributions and Relationships

  • Published:
Quality and Quantity Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Blalock, H. M. (1979). Social Statistics(Revised 2nd edn). New York: McGraw-Hill.

    Google Scholar 

  • Cohen, G. & Java, R. (1995). Memory for medical history: Accuracy of recall. Applied Cognitive Psychology9: 273–288.

    Google Scholar 

  • Cohen, J. (1994). The earth is round (p <0:05). American Psychologist49: 997–1003.

    Google Scholar 

  • De Graaf, P. M., Poortman, A. & Ultee, W. C. (1996). De kwaliteit van retrospectieve beroepsgegevens; een onderzoek op basis van huwelijksaktes. Sociale Wetenschappen39(3): 1–15.

    Google Scholar 

  • DeMaris, A. & Jackson, J. (1986). Nonrespondent characteristics and bias in a study of batterers. Social Service Review60: 460–474.

    Google Scholar 

  • Dex, S. (1995). The reliability of recall data: A literature review. Bulletin de Méthodologie Sociologique49 (December): 58–89.

    Google Scholar 

  • Dijkstra, A. (1981). Ziekteverzuim en non-response: Representativiteit van deelname aan enquê teonderzoek in arbeidsorganisaties ten aanzien van een te verklaren variabele. Gezondheid en Samenleving2: 266–273.

    Google Scholar 

  • Dillman, D. A. (1991). The design and administration of mail surveys. Annual Review of Sociology17: 225–249.

    Google Scholar 

  • Evans, D. S. & Leighton, L. S. (1995). Retrospective bias in the Displaced Worker Surveys. The Journal of Human Resources30: 386–396.

    Google Scholar 

  • Goudy, W. J. (1976). Nonresponse effects on relationships between variables. Public Opinion Quarterly40: 360–369.

    Google Scholar 

  • Goudy, W. J. (1978). Interim response to a mail questionnaire: Impacts on variable relationships. Sociological Quarterly19: 253–265.

    Google Scholar 

  • Goyder, J. (1987). The Silent Minority: Nonrespondents on Sample Surveys. Oxford: Polity Press.

    Google Scholar 

  • Gray, P. G. (1955). The memory factor in social surveys. Journal of the American Statistical Association50: 344–363.

    Google Scholar 

  • Green, J.M. (1996).Warning that reminders will be sent increased response rate. Quality & Quantity30: 449–450.

    Google Scholar 

  • Green, K. E. (1991). Reluctant respondents: Differences between early, late, and nonresponders to a mail survey. Journal of Experimental Education59: 268–276.

    Google Scholar 

  • Groves, R. M. (1987). Research on survey data quality. Public Opinion Quarterly51: S156–S172.

    Google Scholar 

  • Hawkins, D. F. (1975). Estimation of nonresponse bias. Sociological Methods and Research3: 461–488.

    Google Scholar 

  • Hessing, D. J., Elffers, H. & Weigel, R. H. (1988). Exploring the limits of self-reports and reasoned action: An investigation of the psychology of tax evasion behavior. Journal of Personality and Social Psychology54: 405–413.

    Google Scholar 

  • Loftus, E. F., Smith, K. D., Klinger, M. R. & Fiedler, J. (1992). Memory and mismemory for health events. In: J. M. Tanur (ed.), Questions about Questions: Inquiries into the Cognitive Bases of Surveys. New York: Russell Sage Foundation, pp. 102- 137.

    Google Scholar 

  • McKee, D. O. (1992). The effect of using a questionnaire identification code and message about nonresponse follow-up plans on mail survey response characteristics. Journal of theMarket Research Society34: 179–191.

    Google Scholar 

  • Martin, Ch. L. (1994). The impact of topic interest on mail survey response behaviour. Journal of the Market Research Society36: 327–338.

    Google Scholar 

  • O'Muircheartaigh, C. A. (1976). Response errors in an attitudinal sample survey. Quality & Quantity10: 97–115.

    Google Scholar 

  • O'Neill, M. J. (1979). Estimating the nonresponse bias due to refusals in telephone surveys. Public Opinion Quarterly43: 218–232.

    Google Scholar 

  • Pavalko, R. M. & Lutterman, K. G. (1973). Characteristics of willing and reluctant respondents. Pacific Sociological Review16: 463–476.

    Google Scholar 

  • Pearson, R.W., Ross, M. & Dawes, R.M. (1992). Personal recall and the limits of retrospective questions in surveys. In: J. M. Tanur (ed.), Questions about Questions: Inquiries into the Cognitive Bases of Surveys. New York: Russell Sage Foundation, pp. 65–94.

    Google Scholar 

  • Popping, R. (1995). Computing Agreement on Nominal Data: The Computer Program AGREE 6.0. Groningen: iec ProGAMMA.

  • Presser, S. & Traugott, M. (1992). Little white lies and social science models: Correlated response errors in a panel study of voting. Public Opinion Quarterly56: 77–86.

    Google Scholar 

  • Silver, B. D., Anderson, B. A. & Abramson, P. R. (1986). Who overreports voting? American Political Science Review80: 613–624.

    Google Scholar 

  • Stinchcombe, A. L., Jones, C. & Sheatsley, P. (1981). Nonresponse bias for attitude questions. Public Opinion Quarterly45: 359–375.

    Google Scholar 

  • Sudman, S. & Bradburn, N. M. (1974). Response Effects in Surveys: A Review and Synthesis. Chicago: Aldine.

    Google Scholar 

  • Van Goor, H. & Stuiver, B. (1998a). A wave-analysis of distributional bias, substantive bias and data quality in a mail survey among Dutch municipalities. Acta Politica33: 179–196.

    Google Scholar 

  • Van Goor, H. & Stuiver, B. (1998b). Can weighting compensate for nonresponse bias in a dependent variable? An evaluation of weighting methods to correct for substantive bias in a mail survey among Dutch municipalities. Social Science Research27: 481–499.

    Google Scholar 

  • Van Goor, H. & Verhage, A. L. (MS). Recall errors in a study of absence because of illness: Differences in the accuracy of self-reports of sick-leave as a consequence of problems of self-presentation, memory effects, and working conditions.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Van Goor, H., Verhage, A.L. Nonresponse and Recall Errors in a Study of Absence because of Illness: An Analysis of Their Effects on Distributions and Relationships. Quality & Quantity 33, 411–428 (1999). https://doi.org/10.1023/A:1004732502598

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1004732502598

Navigation