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Experimental Designs

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An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...

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Related Experiment Video

Updated: Jul 10, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

Curve-free and model-based continual reassessment method designs.

John O'Quigley¹

¹Department of Mathematics, University of California at San Diego, La Jolla 92093, USA. joquigley@ucsd.edu

|March 14, 2002

Summary

The curve-free method for Phase I clinical trials is operationally equivalent to the model-based continual reassessment method, with no inherent design advantages. Two-stage designs offer an alternative, especially when dealing with informative priors.

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Area of Science:

Biostatistics
Clinical Trial Design
Pharmaceutical Research

Background:

The Continual Reassessment Method (CRM) is a widely used adaptive design for Phase I clinical trials.
Gasparini and Eisele (2000) proposed a curve-free CRM, distinct from traditional model-based approaches.
This study critically evaluates the curve-free method against the standard CRM.

Discussion:

The curve-free method is operationally equivalent to the model-based CRM when non-informative priors are used.
Both methods are sensitive to the choice of arbitrary specification parameters.
Equivalent parameter choices result in identical operating characteristics for both designs.

Key Insights:

The curve-free method does not represent a novel class of designs compared to the model-based CRM.
Reported advantages of curve-free designs stem from favorable parameter choices, not inherent superiority.
Informative priors present a more complex challenge for CRM designs.

Outlook:

Two-stage designs offer potential gains and avoid the complexities of prior specification.
Further research into adaptive designs for complex scenarios, such as informative priors, is warranted.
Standardization of parameter selection for CRM methods could improve comparability.