Abstract
Summary Sequence analysis is widely used in life course research and more recently has been applied by survey methodologists to summarize complex call record data. However, summary variables derived in this way have proved ineffective for post-survey adjustments, owing to weak correlations with key survey variables. We reflect on the underlying optimal matching algorithm and test the sensitivity of the output to input parameters or ‘costs’, which must be specified by the analyst. The results illustrate the complex relationship between these costs and the output variables which summarize the call record data. Regardless of the choice of costs, there was a low correlation between the summary variables and the key survey variables, limiting the scope for bias reduction. The analysis is applied to call records from the Irish Longitudinal Study on Ageing, which is a nationally representative, face-to-face household survey.
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