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Updated: Jul 6, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Evaluating the quality of longitudinal statistical applications in original publications on Alzheimer's disease
Chengjie Xiong1, Yuxiao Tang, Gerald van Belle
1Division of Biostatistics, Washington University, St. Louis, MO 63110, USA. chengjie@wubios.wustl.edu
Background/Aims:
To evaluate the quality of longitudinal statistical applications in published studies on Alzheimer's disease (AD).
Methods:
A 21-item instrument, the Quality of Longitudinal AD Studies (QLADS), was developed by the research team (4 biostatisticians, 1 neuroepidemiologist, and 1 neurologist). All items were extensively discussed within the team for content validity. After pilot testing on 5 publications, the instrument was revised and tested for reliability with a sample of 40 published longitudinal AD studies randomly sampled from MEDLINE.
Results:
Item-specific test-retest reliability coefficients for QLADS ranged from 0.53 to 1.00 with the associated standard error (SE) ranging from 0.02 to 0.13. The test-retest reliability for the overall score over the 21 items was high (intraclass correlation coefficient (ICC) = 0.94, 95% CI 0.90, 0.97). Item-specific inter-rater reliability coefficients for QLADS ranged from 0.46 to 1.00 with the associated SE ranging from 0.07 to 0.18. The inter-rater reliability for the overall score was also high (ICC = 0.87, 95% CI 0.77, 0.93).
Conclusions:
This study indicates that the quality of longitudinal statistical applications in AD publications can be reliably assessed.
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