Tests of Data Quality, Scaling Assumptions, and Reliability of the Danish SF-36

Differences are found indicating advantages of using methods that do not assume a normal distribution of answers as an addition to traditional methods, including polychoric correlations and Spearman correlations.

Abstract

We used general population data (n = 4084) to examine data completeness, response consistency, tests of scaling assumptions, and reliability of the Danish SF-36 Health Survey. We compared traditional multitrait scaling analyses to analyses using polychoric correlations and Spearman correlations. The frequency of missing values was low, except for elderly people and people with lower levels of education. Response consistency was high and compared well with results for the U.S. SF-36. For respondents with computable scales in all eight domains, scaling assumptions (item internal consistency, item discriminant validity, equal item-own scale correlations, and equal variances) were satisfactory in the total sample and in all subgroups. The SF-36 could discriminate between levels of health in all subgroups, but there were skewness, kurtosis, and ceiling effects in many subgroups (elderly people and people with chronic diseases excepted). Concerning correlation methods, we found interesting differences indicating advantages of using methods that do not assume a normal distribution of answers as an addition to traditional methods.