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A strategy to use soft data effectively in randomized controlled clinical trials.

H C Kraemer, S Thiemann

Journal of Consulting and Clinical Psychology

|February 1, 1989

Summary

This study defines soft data and demonstrates how an intensive design using the slope of response over time enhances randomized clinical trials. This method boosts statistical power and sample retention without needing larger participant groups.

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Area of Science:

Biostatistics
Clinical Trial Design
Measurement Error

Background:

Soft data, characterized by significant intrasubject variability, are crucial in clinical research.
Intrasubject variability arises from measurement errors and inconsistent participant responses.
Optimizing the analysis of soft data is essential for robust clinical trial outcomes.

Purpose of the Study:

To define soft data and its implications in randomized clinical trials.
To propose an intensive design and specific outcome measure for analyzing soft data.
To evaluate the impact of this approach on statistical power and sample retention.

Main Methods:

Defined soft data, emphasizing intrasubject variability from measurement error and response inconsistency.

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Employed an intensive study design.

Utilized the slope of response on time as the primary outcome measure.

Main Results:

The intensive design maximized sample retention.
The slope of response on time decreased within-group variability.
Statistical test power was maximized without increasing sample size.

Conclusions:

An intensive design with the slope of response on time is an effective strategy for analyzing soft data in clinical trials.
This approach enhances statistical efficiency by reducing variability and improving sample retention.
The methodology offers a powerful tool for randomized clinical trials involving measures with high intrasubject variability.