Abstract
True-value theory (Bechtel, 2010), as an extension of randomization theory, allows arbitrary measurement errors to pervade a survey score as well as its predictor scores. This implies that true scores need not be expectations of observed scores and that expected errors need not be zero within a respondent. Rather, weaker assumptions about measurement errors over respondents enable the regression of true scores on true predictor scores. The present paper incorporates Sarndal-Lundstrom (2005) weight calibration into true-value regression. This correction for non-response is illustrated with data from the fourth round of the European Social Survey (ESS). The results show that a true-value regression coefficient can be corrected even with a severely unrepresentative sample. They also demonstrate that this regression slope is attenuated more by measurement error than by non-response. Substantively, this ESS analysis establishes economic anxiety as an important predictor of life quality in the financially stressful year of 2008.
Highlights
The collection of micro data, with opinion polls, has become a world-wide commercial and governmental activity
The present paper extends the reach of true-value theory by treating unit non-response with Sarndal-Lundstrom (2005) calibration of sampling weights
The effect of economic anxiety on life quality is estimated from a criterion sample and a non-representative sub-sample
Summary
The collection of micro data, with opinion polls, has become a world-wide commercial and governmental activity. The corrective value of SL calibration is demonstrated with data from the fourth round of the European Social Survey (ESS) This exercise confirms economic anxiety as an important predictor of life quality in the global financial crisis of 2008. The effect of economic anxiety on life quality is estimated from a criterion sample and a non-representative sub-sample This exercise demonstrates the corrective power of SL weight calibration in the presence of unit non-response.
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