# Presentation: 030648

## Group-Randomized Trials

- Distinguishing characteristics
- The unit of assignment is an identifiable group.
- Different groups are allocated to each condition.
- The units of observation are members of the groups.
- The number of groups allocated to each condition is usually limited.

## Group-Randomized Trials

- Primary advantages
- Randomization provides the statistical basis for the assumption of independence at the group level.
- With proper randomization and enough groups...
- Potential sources of bias are fairly distributed across the study conditions.
- Inferences based on a valid analysis can be as strong as those obtained from a randomized clinical trial.
- For this reason, the GRT is the gold standard for design in public health and medicine when allocation of identifiable groups is necessary.

## Group-Randomized Trials

- Primary disadvantages
- There is extra variation attributable to the groups.
- This increases the standard error of the intervention effect.
- The number of groups is often limited.
- This limits error degrees of freedom and reduces the effectiveness of randomization.
- Together, these problems can threaten internal validity and power in small trials.
- At the same time, logistics and cost can threaten the viability of large trials.

## The Warning

*Randomization by cluster accompanied by an analysis appropriate to randomization by individual is an exercise in self-deception, however, and should be discouraged.*
- 								Cornfield (1978)

## Progress Addressing the Major Disadvantages

- Extra variation
- Regression adjustment for covariates
- Modeling time
- Limited degrees of freedom
- Proper planning
- Borrowing information from similar studies

## Other Recent Methodological Developments

- Analysis methods
- Small sample corrections for GEE
- Methods for survival analysis
- Improved power for permutation tests
- Mediation models
- Missing data
- Nonlinear mixed models
- Reference
- Murray, D. M., Varnell, S. P., & Blitstein, J. L. (2004). Design and analysis of group-randomized trials: A review of recent methodological developments. _AJPH_, _94_(3), 423-432.

## State of the Practice

- How are we doing?
- Sample size estimation
- Analysis methods
- 58 GRTs published in AJPH and Prev Med, 1998-2002
- Reference
- Varnell, S., Murray, D. M., Janega, J. B., & Blitstein, J. L. (2004). Design and analysis of group-randomized trials: A review of recent practices. _AJPH,_ _94_(3), 393-399.

## Findings

- Only 16% reported evidence of using appropriate methods for sample size calculations.
- Similar to 19% in Simpson et al., 1995 review
- 54% reported only analyses judged to be appropriate.
- Similar to 57% in Simpson et al., 1995 review
- That figure rises to 68% if we use Simpson et al.'s criteria
- 19% reported only analyses deemed invalid.
- 26% reported a mix of methods.
- Some progress since 1995, but still need for improvement, especially with regard to more recent findings.

## Summary and Recommendations

- Many questions do not require a GRT.
- Formative research
- Other questions may require a GRT design but not a full-blown GRT analysis.
- Feasibility or preliminary evidence of efficacy
- Here, estimate effect and/or ICC, but avoid causal inference.
- Other questions cannot be addressed using a GRT.
- Policy change at large aggregate level
- Use quasi- or natural experiments if they will provide useful information efficiently.
- Do not ignore the design and analytic challenges inherent in nested designs.
- For efficacy studies, use individual-level randomization whenever possible.

## Summary and Recommendations

- Reserve GRTs for situations in which...
- Experimental evidence is needed for causal inference,
- Individual randomization is not possible,
- There is preliminary evidence for feasibility and efficacy,
- There is sufficient information available to size the study.
- Use the available tools to do the best job possible.
- Match the design to the research question.
- Use appropriate analysis methods.
- Ensure adequate power.
- Choose a valid analysis that minimizes the SE for the intervention effect.
- Build in sufficient replication at the group level.

## Slide 11

## Slide 12