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Trials which randomize practices I: how should they be analysed?

S M Kerry¹, J M Bland

¹Division of General Practice and Primary Care, St George's Hospital Medical School, London, UK.

Family Practice

|April 4, 1998

Summary

When analyzing general practice trials, correctly accounting for practice-level randomization is crucial. Failure to do so can result in misleading statistical significance and confidence intervals (CIs).

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Area of Science:

Biostatistics
General Practice Research

Background:

Intervention trials in general practice often require randomization at the practice level, not the individual patient level.
This clustering effect must be appropriately addressed during statistical analysis.

Purpose of the Study:

To demonstrate the pitfalls of ignoring practice-level randomization, including inflated statistical significance and overly narrow confidence intervals (CIs).
To present summary measures per practice as a straightforward analytical approach.

Main Methods:

The statistical challenges are illustrated using a case study from a general practice intervention trial.
The analysis focuses on the impact of the unit of analysis on study outcomes.

Main Results:

Improper analysis can lead to spurious statistical significance, suggesting treatment effects that do not exist.
Incorrect methods produce confidence intervals that are narrower than appropriate, potentially leading to false conclusions about precision.

Conclusions:

The selection of the appropriate unit of analysis is critical, particularly when dealing with a large number of patients per practice or substantial inter-practice variability.
Accurate statistical methods are essential for reliable interpretation of general practice intervention trial results.

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