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Related Concept Videos

Randomized Experiments01:13

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

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Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
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Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

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Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
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Stratified Sampling Method01:16

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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Crossover Experiments01:16

Crossover Experiments

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Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
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Stratified randomization for platform trials with differing experimental arm eligibility.

Subodh Selukar1, Susanne May1, Dave Law2

  • 1Department of Biostatistics, University of Washington, Seattle, WA, USA.

Clinical Trials (London, England)
|August 23, 2021
PubMed
Summary
This summary is machine-generated.

Platform trials efficiently compare multiple treatments. New methods extend stratified randomization for platform trials with varying experimental arm eligibility, improving participant allocation and trial efficiency.

Keywords:
COVID-19Platform trialsSARS-CoV-2oncologystratified randomizationvarying eligibility

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmaceutical Research

Background:

  • Platform trials enable efficient comparison of multiple experimental agents against a standard of care.
  • They offer flexibility to adapt to evolving scientific understanding by adding or removing experimental arms.
  • Differing eligibility criteria for experimental arms pose challenges for traditional stratified randomization.

Purpose of the Study:

  • To propose extensions of conventional stratified randomization methods for platform trials.
  • To address the challenge of differing eligibility criteria across experimental arms.
  • To maintain balanced participant allocation in complex platform trial designs.

Main Methods:

  • Modified block randomization incorporating experimental arm eligibility as a stratifying variable.
  • Adjusted imbalance score calculations for dynamic balancing using pairwise comparisons.
  • Balancing on prespecified stratification variables consistent across all experimental arms.

Main Results:

  • Proposed methods provide a framework for stratified randomization in platform trials with heterogeneous eligibility.
  • Worked examples illustrate the application of the extended randomization techniques.
  • A formula is provided to quantify efficiency loss due to varying eligibility.

Conclusions:

  • The proposed extensions facilitate the implementation of platform trials with diverse experimental arm eligibility.
  • These methods enhance the robustness and efficiency of platform trial designs.
  • Improved randomization strategies are crucial for advancing research in rapidly developing fields.