temporal design considerations
DESCRIPTION
A useful reminder of why and when it is important to pivot a longitudinal design on aspects of the system being studied.TRANSCRIPT
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Longitudinal Design Considerations
Kevin CumminsAddictions Research Seminar
University of California, San Diego
August 29, 2006
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Objective
• Provoke a discussion about the needs and realities of designing and executing a longitudinal research project.
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Outline
• Introduction
• Basic Structural Variations in Longitudinal Studies
• Considerations in Temporal Design
• Conclusion
• Discussion
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Longitudinal Studies
• Defining feature: outcome variables measured on more than one occasion.
• Fundamental statistical feature: measurements will be correlated.
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Cross-sectional Data
From Frees 2005
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Longitudinal Structure Visualized
From Frees 2005
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Benefits
• Attrition bias• Logistic complexities
and expense• Delayed results
• Dynamic relationships revealed.
• Improved estimation efficiency.
• Provide descriptions of individual development patterns.
• Considered helpful in establishing causation.
Drawbacks
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Evidence for Causality
• Appropriate correlations/association
• Consistency in various environments• Specificity (cause leads to a single effect)• Dose-Response• Biological plausibility
• Temporality (cause precedes effect)
• Experimental evidence (causality tested)
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Outline
• Introduction
• Basic Structural Variations in Longitudinal Studies
• Considerations in Temporal Design
• Conclusion
• Discussion
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Experimental Longitudinal Studies (Most RCTs)
• Gold standard
• Efficiency and effectiveness require thoughtful treatment assignment and measurement regime
• Interpretation often limited by the sampling frame and the non-representative clinical environments
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Basic Experimental Designs
• Classic
• Classic with baseline
• Classic with longitudinal follow-up
• Factorial
• Cross-over design
• Solomon design
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Observational Longitudinal
• Can provide developmental description of phenomenon.
• Can provide correlation, consistency, dose-response, and temporality evidence of causation.
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Issues in Longitudinal Studies
• Period Effects
• Cohort Effects
• Measurement Effects
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Period Effect
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Cohort Effect
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Multiple Cohort Design
• Designs that follow multiple age cohorts through the same developmental time frames.
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What’s Going On?
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Detecting Period Effect
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Measurement Effect
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First Considerations
• Do you design for:• Evidence of causation,• Period effects,• Cohort effects,• Measurement effects?
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Outline
• Introduction
• Basic structural variations in longitudinal studies
• Considerations in temporal design
• Conclusion
• Discussion
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Analysis of Longitudinal Data: The Integration of Theoretical Model,
Temporal Design, and Statistical ModelLinda M. Collins
The Methodology Center andDepartment of Human Development & Family Studies
Penn State
Presented at the CALDAR Summer Institute, Los Angeles, CA August 14, 2006
Much of this talk comes from Linda Collin’s work
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Take Home from Collins 2006
• Ideal longitudinal research should be characterized by a tight integration of:
1) a well articulated theoretical model,
2) an appropriate temporal design,
3) and a statistical model that operationalizes the theoretical model.
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Theoretical Model of Change• General shape• Periodicity• Function of
– Calendar time/age/stage– Another changing variable– Or self-regulating
• Covariates– Time-invariant– Time-varying
• Is relation with covariates time-varying?• What are the magnitudes of the various patterns?• Is the response variable quantitative or qualitative?
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Temporal Design
• Timing, frequency, spacing of observations in a longitudinal study
• What makes a good temporal design?
– It provides a clear view of the change phenomenon of interest and articulation of aspect of interest.
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Comparison Features
• Property– Overall value/Magnitude– Extreme value– Delay in response
– Rate of change– Final level
– Delay in response– Overall Functional Form
• Summary Measure– Mean or AUC– Max/Min– Time to max/min or
change point
– Regression coef.
– Final value/relative difference
– Time to threshold– Linear/Nonlinear/Semipa
rametric statistical model
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Temporal Design
• Should be chosen on basis of theoretical model• Can’t observe change that occurs
– Before study begins– After study concludes– Between observations
• More frequent measurement called for when– Change is rapid– Curvilinear response (min. 4-5 time points)
• Timing may be critical when– Periodicity– Important event expected
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Pattern vs. Grain
• Other effects of using a measurement interval that is too wide:
– Important complexities of growth curves may go undetected
– Cannot detect important effects– Cannot model mediation properly– Oversimplify change processes and their relations
with other processes– Entire stages may be missed from stage-sequential
models, and rates of transitions may be inaccurate
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Get More Time Points
– When designing studies, choose the measurement interval in relation to the characteristics of the phenomena of interest
• If they are fast-moving, use a short interval
• If they are slow-moving, a longer interval is OK
– In most cases, this will lead to consideration of a shorter measurement interval
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Yeah, Right…
• Problems with more frequent measurement:– Available resources– Logistical difficulties– Measurement effects
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Temporal Design: Collins’ Note
• The choice of measurement interval should always be justified on scientific grounds
• Logistical considerations play a role, but any write-up should show that the design is a reasonable one given the phenomena of interest
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Outline
• Introduction
• Basic Structural Variations in longitudinal studies
• Considerations in Temporal Design
• Conclusion
• Discussion Match Good Temporal Design to Good Data Design
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Data Formats for Longitudinal Studies
Long Form
Wide Form
Subject ID Tx Response0 Response22 Response34 Response50 Response51 Response741 1 0.07 0.95 0.91 . . .2 2 0.89 0.93 0.47 . 0.493 1 0.28 . . . . .4 2 0.30 . 0.49 . 0.18 .
Time (days) Subject ID Tx Response0 1 1 0.0722 1 1 0.9534 1 1 0.910 2 2 0.8922 2 2 0.9350 2 2 0.4774 2 2 0.490 3 1 0.2822 3 1 0.050 4 2 0.3034 4 2 0.4951 4 2 0.18
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Benefits of Long Format
• Write syntax once!
• Recognize temporal inconsistencies quickly
• Take advantage of contemporary analysis techniques. Distinct “waves” not necessary
• Easy to create a wide file from long format, but not always vise versa
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Outline
• Introduction
• Basic Structural Variations in longitudinal studies
• Considerations in Temporal Design
• Conclusion
• Discussion
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Collins’ Concluding Remarks
Two comments I’ve heard when I talk about temporal design:
(1) EVERYBODY PAYS ATTENTION TO TEMPORAL DESIGN ALREADY
How many research reports in journal articles, or research proposed in grant proposals, justify the temporal design on anything but logistical grounds?
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Collins’ Concluding remarks
Two comments I’ve heard when I talk about temporal design:
(2) HOW CAN I BE EXPECTED TO FIND THE RESOURCES TO CARRY OUT THE IDEAL TEMPORAL DESIGN?
Usually you can’t, but it is still useful to articulate the ideal.
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Outline
• Introduction
• Basic Structural Variations in longitudinal studies
• Considerations in Temporal Design
• Conclusion
• Discussion