Introduction

In the past, many surveys have reported the response rate (see Chapter 20) as the only measure of the quality of the data from a survey. Although the response rate could be considered a necessary measure of data quality, it is by no means a sufficient definition of data quality. The response rate, after all, measures only the proportion of the attempted sample from which what are regarded as complete responses were obtained. It is certainly true that one can immediately assume that a low response rate is likely to mean that the data will be subject to substantial nonresponse bias and may be far from a representative sample of the target population. However, it does not follow that a high response rate indicates good-quality data.

As a general rule, there are a few measures of data quality that can be applied to all surveys, and there are a few measures of data quality that are specific to specific types of surveys. In this chapter, I deal first with some general measures of quality, and then discuss some specific measures that may apply to only a specific type of survey. The latter are provided only as examples, to assist the reader to develop such measures for the specific type of survey with which he or she may be concerned. Following this the chapter deals with validation surveys, and it concludes by proposing a checklist of measures that would assess the overall quality of the survey effort.