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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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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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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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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure 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.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Blinding01:11

Blinding

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Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
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Odds Ratio01:09

Odds Ratio

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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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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.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
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Updated: Sep 9, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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A randomization strategy for a cluster-randomized controlled trial with variable operating room availability.

Sheau-Chiann Chen1, Heidi Chen1, Rafael Paez2

  • 1Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.

Contemporary Clinical Trials
|August 30, 2025
PubMed
Summary
This summary is machine-generated.

This study optimized diagnostic bronchoscopy trials by stratifying operating room assignments. A novel randomization method significantly reduced patient assignment imbalance, improving resource allocation for clinical outcome comparisons.

Keywords:
Block sizeClusterPermuted block randomizationSimple randomizationStratification

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Area of Science:

  • Medical research methodology
  • Pulmonology
  • Clinical trial design

Background:

  • Comparing diagnostic bronchoscopy platforms requires robust trial designs.
  • Resource limitations in operating rooms (ORs) and equipment can challenge patient randomization.
  • Cluster randomized controlled trials (cRCTs) are suitable for pragmatic comparisons but need careful allocation strategies.

Purpose of the Study:

  • To compare clinical outcomes of two diagnostic bronchoscopy approaches (Platform A and Platform B).
  • To develop and evaluate an effective randomization strategy for a cluster randomized controlled trial (cRCT) given resource constraints.
  • To minimize patient assignment imbalance between the two platforms.

Main Methods:

  • A single-center, open-label, pragmatic, non-inferiority cRCT was designed.
  • Clusters were defined as operating room (OR) days.
  • A permuted-block randomization method, stratified by OR availability, was simulated and evaluated for assignment balance.

Main Results:

  • Stratification by OR availability significantly reduced assignment imbalance (mean imbalance = -0.006, SD = 0.690) compared to stratification by weekdays (mean imbalance = 0.044, SD = 1.110).
  • The proposed method effectively minimized the difference in patient enrollment between Platform A and Platform B.
  • The strategy optimized the allocation of limited OR and bronchoscopy platform resources.

Conclusions:

  • A permuted-block randomization method stratified by OR availability is an effective strategy for cRCTs with resource limitations.
  • This innovative design improves the balance of patient assignments in diagnostic bronchoscopy trials.
  • The findings support optimized resource allocation and reliable clinical outcome comparisons in pragmatic trials.