Report on Types of Errors Produced by Questionnaires in Research

This report examines the types of errors produced by questionnaires in public administration research. It references Gonzalez's work on improving data quality awareness within federal statistical agencies, highlighting the importance of effective questionnaire design, testing, and evaluation. The report discusses the role of cognitive laboratories in addressing measurement errors and the evolution of data collection methods from paper-based questionnaires to computer-assisted personal interviews (CAPI-CATI). Additionally, it explores errors associated with telephone surveys and the efforts of federal agencies to reassess data collection methods to enhance data quality, minimize biases, and ensure broader coverage. The report concludes by emphasizing the investment in computer-assisted survey forms to minimize biases and improve interactions with respondents.

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Public administration
Types of errors produced by questionnaires
Name of Student
Institutional Affiliation
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Types of errors produced by questionnaires
(Gonzalez, 1994, pp.12-17) ellaborates on improving the awareness of data quality in the
Federal Statistical agencies outlines the errors of measurement associated with the use of
questionnaires. The author illustrates three aspects for coming up with effective questionnaires as
developing the questions, testing, and evaluating the questionnaire. In research, the quality of
data to be collected determines the reliability of the findings and the degree of projecting the
results to a larger population. This calls for an establishment of an effective data collection
method which begins with the identification of the nature of data to be collected in relation to the
research objectives and question.
The article provides a practical guidance on improving the use of survey questionnaires
for data collection by the federal agencies and their contractors. The cognitive aspects of survey
methodology was identified to be used in the article by the committee of the national statistics by
formation of the cognitive laboratories to address the measurements of the errors associated with
the survey questionnaires used by the federal agencies of the United States (Koskey, Sondergeld,
Stewart, and Pugh, 2018, pp.95-122). These laboratories were relied on for testing, developing,
and improving the quality of the survey data as well as for developing a theoretical foundation
that aimed at minimizing the sampling errors in designing the survey study.
Additionally, the vulnerability shown by the completed projects indicated the factual
biases in the used questionnaires that demanded pre-testing of questions and the procedures in
these laboratories to outlay an extensive set of questionnaires before fielding a survey for the
other studies. The pre-testing process involved the engagement of the informal interviews for
small experimental research to the main large-scale research studies. The article elaborates that

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this system was effective as it led to the change in data collection mode from the questions on
paper to computed aided personal interviews (the CAPI-CATI data collection). Another source
of errors was through the use of questionnaires assessed through the use of the telephones to
collect data (Brace, 2018). The author presents an error in the profiles provided by the
respondents due to the inconsistencies in the data collected. According to the study done on the
nation crime survey, the findings indicated that the differences in the response provided by the
victims depended on the mode of interviews implemented. Additionally, the survey on the rate of
unemployment in the United States in the 1980s indicated that those collected through the paper-
and-pencil questionnaires showed a higher percentage than those collected using the traditional
data collection methods.
With the increase in the data collection using questionnaires filled via telephone, the
federal agencies began a campaign to reassess other methods regardless of the time taken and the
financial consideration that would lead to coverage of a bigger coverage of samples/population,
enhanced cooperation of the participants, minimized biases, and effective interviewer
contributions to the data variance among other aspects of data quality (Nardi, 2018). This led to
investment in the computer assisted survey forms of questionnaires that could be installed on
small computers and filled by researchers during the actual visits in the field where they could
interact with respondents, thus minimizing the potential occurrence of biases.

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References
Brace, I. (2018). Questionnaire design: How to plan, structure and write survey material for
effective market research. Kogan Page Publishers.
González, M. E. (1994). Improving data quality awareness in the United States federal statistical
agencies. The American Statistician, 48(1), 12-17.
Koskey, K. L., Sondergeld, T. A., Stewart, V. C., & Pugh, K. J. (2018). Applying the mixed
methods instrument development and construct validation process: The transformative
experience questionnaire. Journal of Mixed Methods Research, 12(1), 95-122.
Nardi, P. M. (2018). Doing survey research: A guide to quantitative methods. Routledge.