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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