scholarly journals An Empirical Total Survey Error Decomposition Using Data Combination

2019 ◽  
Author(s):  
Bruce Meyer ◽  
Nikolas Mittag
Author(s):  
Marcus E. Berzofsky ◽  
Andrew Moore ◽  
G. Lance Couzens ◽  
Lynn Langton ◽  
Chris Krebs

We use a total survey error approach to examine and make recommendations on how to adjust for non-sampling error in longitudinal, mixed-mode surveys. Using data from the National Crime Victimization Survey (NCVS), we examine three major sources of non-sampling error: telescoping, mode effects, and fatigue. We present an assessment of each source of error from a total survey error perspective and propose alternative adjustments to adjust better for this error. Findings suggest that telescoping and fatigue are likely sources of error in the NCVS, but the use of mixed-modes is not. Furthermore, both telescoping and fatigue are present in longitudinal surveys and accounting for one but not the other results in estimates that under- or overestimate the measures of interest—in this case, the rate of crime in the United States.


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