| |
Centre for Policy on Ageing | |
 | |
|
Data harmonization in aging research
— not so fast | | Author(s) | Margaret Gatz, Chandra A Reynolds, Deborah Finkel |
| Journal title | Experimental Aging Research, vol 41, no 5, October-December 2015 |
| Publisher | Taylor and Francis, October-December 2015 |
| Pages | pp 475-495 |
| Source | http://www.tandfonline.com |
| Keywords | Ageing process ; Depression ; Assessment procedures for mental patients ; Health [elderly] ; Measurement ; Standardisation ; United States of America. |
| Annotation | Harmonising measures in order to conduct pooled data analyses has become a scientific priority in ageing research. Retrospective harmonisation where different studies lack common measures of comparable constructs presents a major challenge. This study compared different approaches to harmonisation with a crosswalk sample (a within subject design) who completed multiple versions of the measures to be harmonised. Through online recruitment, 1061 participants aged 30 to 98 answered two different depression scales, and 1065 participants answered multiple measures of subjective health. Rational and configural methods of harmonisation were applied, using the crosswalk sample, to determine their success. Empirical item response theory (IRT) methods were applied in order to empirically compare items from different measures as answered by the same person. For depression, IRT worked well to provide a conversion table between different measures. The rational method of extracting semantically matched items from each of the two scales proved an acceptable alternative to IRT. For subjective health, only configural harmonisation was supported. The subjective health items used in most studies form a single robust factor. The authors conclude that caution is required in ageing research when pooling data across studies using different measures of the same construct. Of special concern are response scales that vary widely in the number of response options, especially if the anchors are asymmetrical. A crosswalk sample that has completed items from each of the measures being harmonised allows the investigator to use empirical approaches to identify flawed assumptions in rational or configural approaches to harmonising. (RH). |
| Accession Number | CPA-160127225 A |
| Classmark | BG: ENR: DA:4C: CC: 3R: 3W: 7T |
Data © Centre for Policy on Ageing |
|
| ...from the Ageinfo database published by Centre for Policy on Ageing. |
| |
|