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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
Simple...
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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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Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

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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 subjects...
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Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

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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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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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Related Experiment Video

Updated: Apr 27, 2026

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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Challenges of cluster randomized trials.

Michael J Campbell1

  • 1Medical Statistics Group, ScHARR, University of Sheffield, S1 4DA, UK.

Journal of Comparative Effectiveness Research
|June 28, 2014
PubMed
Summary
This summary is machine-generated.

Cluster randomized trials, which randomize groups instead of individuals, are increasingly used. Recent innovations focus on sample size, missing data, bias reduction, ethics, and the stepped wedge design, alongside reporting guidelines.

Keywords:
cluster randomized trialscovariate adjustmentethicsmissing datarecruitment biassample sizestepped wedge

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Area of Science:

  • Biostatistics
  • Clinical Trials Methodology
  • Epidemiology

Background:

  • Cluster randomized trials (CRTs) are gaining prominence in research.
  • Innovations in CRT methodology are crucial for robust study design.

Purpose of the Study:

  • To highlight recent advancements in cluster randomized trial design and analysis.
  • To discuss critical aspects of reporting for cluster randomized trials.

Main Methods:

  • Review of recent innovations in cluster randomized trial methodology.
  • Illustrative examples of new developments in the field.
  • Discussion of ethical considerations and reporting standards.

Main Results:

  • Significant developments in sample size calculation for CRTs.
  • Advancements in handling missing data within cluster designs.
  • Introduction and discussion of the stepped wedge design.
  • Strategies for minimizing recruitment bias in CRTs.
  • Exploration of ethical considerations specific to CRTs.

Conclusions:

  • Recent innovations enhance the precision and feasibility of cluster randomized trials.
  • Improved reporting guidelines are essential for the transparent and accurate dissemination of CRT findings.