Title: Separation of Longitudinal Change from ReTest Effect using a MultipleGroup Latent Growth Model
1Separation of Longitudinal Change from Re-Test
Effect using a Multiple-Group Latent Growth Model
- Richard N. Jones, John N. Morris, Adrienne N.
Rosenberg, Research and Training Institute,
Hebrew Rehabilitation Center for Aged, Research
and Training Institute, Boston MA
Data acquisition and research supported by the
NIA and NINR
2Objective
- Describe a commonly occurring challenge in
longitudinal studies of cognitive aging the
re-test effect - Present a general latent variable modeling
framework for statistically separating aging and
re-test effects - Demonstrate the modeling approach in real data
(ACTIVE Cognitive intervention study)
3Hypothesized Longitudinal Course
4Hypothesized and Observed Longitudinal Course
5Bias in Estimate of Baseline Level and Change
6Hypothesized Longitudinal Course
7Latent Growth Model
8Latent Growth Curve Model for Linear Change
9Hypothesized Longitudinal Course
10Latent Growth Curve Model for Linear Changewith
second intercept (learning factor)
11Adding Background and Explanatory Variables
12Example ACTIVE
- Advanced Cognitive Training for Vital and
Independent Elderly - Six sites (AL, IN, MA, MI, MD, PA)
- Random assignment to one of four intervention
arms, 4-group pre-post design - Speed of Processing, Memory, Logical Reasoning,
No Training Control - Healthy older adults (n2,428) aged 65-83
13Outcome Measure
- Speed of Processing Composite
- Ball, et al. Jama, 2002 2882271-81.
- Regression-method factor score for multiple
speeded tests - Based on minimum stimulus duration at which
participants could identify and localize
information with 75 accuracy, under different
cognitive demand conditions - Lower is better (faster speed of processing)
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15Measurement Schedule
16Speed as a Function of Age (Baseline only, All
Participants)
17Conflicting Estimates of Change
18Multiple Group LGM
- Use age as a cohort indicator
- Model change as a function of age rather than
study time - Assume (initially) no cohort differences in
- growth
- re-test effects, and the
- influence of background variables
19Cross-Sequential Cohort Design
20Hypothesized and Observed Longitudinal Course
21Mean Scores On Repeat Testing(Non-Speed Trained
Group)
22Parameterization of Multiple Group LGM
23Parameterization of Multiple Group LGM
24Parameterization of Multiple Group LGM
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27Results Cohort-Specific and Model Implied
Trajectories
28Hypothesized Longitudinal Course
29Conclusion
- MGLGM one method for modeling re-test effect and
aging effect separately - LGM feature of freely estimating time scores
useful for capturing residual re-test effects - Examine relationship of background
characteristics and variance in retest and aging
effects - Relationship of retest and learning to clinically
meaningful outcomes
30Acknowledgement
- ACTIVE study (Advanced Cognitive Training for
Independent and Vital Elderly) is a multi-site
collaborative cognitive intervention trial
supported by the National Institute on Aging and
the National Institute on Nursing Research. - Sharon Tennstedt is the principal investigator at
the coordinating center, New England Research
Institutes, Watertown, Massachusetts (AG14282). - The principal investigators and field sites
include - Karlene Ball, University of Alabama at Birmingham
(AG14289) - Michael Marsiske, Institute on Aging, University
of Florida, Gainesville (AG14276) - John Morris, Hebrew Rehabilitation Center for
Aged Research and Training Institute, Boston
(NR04507) - George Rebok, Johns Hopkins University Bloomberg
School of Public Health (AG14260) - Sherry Willis, Penn State University, Gerontology
Center (AG14263). - David Smith was the principal investigator at
Indiana University School of Medicine,
Regenstrief Institute, Indianapolis (NR04508) at
the time of initial award, currently Fred
Unverzagt is currently the principal
investigator.
31Age Differences in MSQ Score (Baseline EPESE)
b -.02 SD units per year
Baseline data from EPESE/ICPSR public use data
file, baseline data only, listwise complete on
Mental Status Questionnaire (MSQ) scores at
first, fourth and seventh assessment
32Age Differences in MSQ Score (Baseline EPESE)
b -0.02 SD/year
b -0.10 SD/year
b -0.06 SD/year
Baseline data from EPESE/ICPSR public use data
file, baseline data only, listwise complete on
Mental Status Questionnaire (MSQ) scores at
first, fourth and seventh assessment