Total survey error explained

In survey sampling, Total Survey Error includes all forms of survey error including sampling variability, interviewer effects, frame errors, response bias, and non-response bias. Total Survey Error is discussed in detail in many sources including Salant and Dillman.[1]

Definition

Total Survey Error is the difference between a population parameter (such as the mean, total or proportion) and the estimate of that parameter based on the sample survey or census. It has two components: sampling error and nonsampling error. Sampling error, which occurs in sample surveys but not censuses results from the variability inherent in using a randomly selected fraction of the population for estimation. Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection, data processing and estimation methods.

Sources of nonsampling error

The survey literature decomposes nonsampling errors into five general sources or types: specification error, frame error, nonresponse error, measurement error, and processing error.

References

  1. Salant, Priscilla, I. Dillman, and A. Don. How to conduct your own survey. No. 300.723 S3.. 1994.
  2. Alwin, D. F. (2007). Margins of error: A study of reliability in survey measurement. Hoboken, Wiley
  3. Saris, W. E. and Gallhofer, I. N. (2014). Design, evaluation and analysis of questionnaires for survey research. Second Edition. Hoboken, Wiley.

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