Method variation in the impact of missing data on response shift detection-Reference-Cited by-同舟云学术

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Method variation in the impact of missing data on response shift detection

Published:2014-07-10 Issue:3 Volume:24 Page:521-528
ISSN:0962-9343
Container-title:Quality of Life Research
language:en
Short-container-title:Qual Life Res

Author:

Schwartz Carolyn E.,Sajobi Tolulope T.,Verdam Mathilde G. E.,Sebille Veronique,Lix Lisa M.,Guilleux Alice,Sprangers Mirjam A.G.

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health

Link

http://link.springer.com/content/pdf/10.1007/s11136-014-0746-0.pdf

Reference54 articles.

1. Lewis-Beck, M. (2002). Series editor’s introduction. Missing data (pp. v–vi). Thousand Oaks, CA: Sage.

2. Becker, H., Stuifbergen, A., Rogers, S., & Timmerman, G. (2000). Goal attainment scaling to measure individual change in intervention studies. Nursing Research, 49(3), 176–180.

3. Ahmed, S., Mayo, N., Scott, S., Kuspinar, A., Hum, S., & Schwartz, C. E. (2011). Using latent trajectory analysis to detect response shift in general health among multiple sclerosis patients. Quality of Life Research, 20(10), 1555–1560.

4. King-Kallimanis, B. L., Oort, F. J., Nolte, S., Schwartz, C. E., & Sprangers, M. A. G. (2011). Using structural equation modeling to detect response shift in disability and QOL scores of multiple sclerosis patients. Quality of Life Research, 20(10), 1527–1540.

5. Li, Y., & Schwartz, C. E. (2011). Using classification and regression tree to examine evidence of quality of life response shift in patients with multiple sclerosis. Quality of Life Research, 20(10), 1543–1553.

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