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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

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...
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

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...
Blinding01:11

Blinding

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.
Group Design02:01

Group Design

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 the two are due to...

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Related Experiment Videos

Minimal Sufficient Balance Randomization and Site-Specific Treatment Allocation Imbalance in Multicenter Acute Stroke

Timofei Biziaev1, Michael D Hill1,2, Hannah Johns3

  • 1Department of Community Health Sciences (T.B., M.D.H., B.K.M., T.T.S.), University of Calgary, Canada.

Stroke
|May 8, 2026
PubMed
Summary

Minimal sufficient balance (MSB) randomization preserves treatment allocation randomness and covariate balance in acute stroke trials. However, site-specific imbalance persists at low-enrolling sites, regardless of the randomization method used.

Keywords:
algorithmsprobabilityprognosisrandom allocationstroke

Related Experiment Videos

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Neurology

Background:

  • Optimal randomization schemes aim for treatment allocation randomness, group size balance, and prognostic covariate balance.
  • Covariate-adaptive randomizations, like minimal sufficient balance (MSB), have shown accuracy in achieving covariate balance in acute stroke trials.
  • This study compares covariate-adaptive techniques against simple and block randomization for minimizing site-specific treatment group imbalance in multicenter acute stroke trials.

Purpose of the Study:

  • To evaluate the performance of covariate-adaptive randomization techniques against simple and block randomization.
  • To assess the minimization of site-specific treatment group imbalance in multicenter acute stroke trials.
  • To determine the effectiveness of MSB algorithms in preserving treatment allocation randomness and covariate balance.

Main Methods:

  • Monte Carlo simulations were employed to assess various MSB versions (stratified, unstratified, common scale, common scale group-size) against permuted block and simple randomization.
  • Simulations varied the number of sites, enrollment distribution, baseline covariates (sex, age, NIH Stroke Scale, large vessel occlusion), and sample size.
  • Performance was evaluated using the probability of covariate imbalance, proportion of biased allocations, and group allocation ratios at interim and final stages.

Main Results:

  • MSB algorithms demonstrated a significantly lower probability of observing covariate imbalance (0-2%) compared to simple or permuted block randomization (21%) at n=600 with 20 sites.
  • While MSB improved site-specific imbalance, it persisted in low-enrolling sites across all randomization schemes.
  • Treatment allocation randomness and group balance were maintained in high-volume sites under MSB.

Conclusions:

  • MSB algorithms effectively preserve overall treatment allocation randomness and covariate balance in acute stroke trials.
  • Site-specific treatment group imbalance remains a challenge at low-enrolling sites, irrespective of the randomization method.
  • Logistical strategies to minimize low enrollment across sites are recommended prior to initiating multicenter acute stroke trials.