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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...
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...
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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.
Cochran's Q Test01:17

Cochran's Q Test

Cochran's Q Test is a nonparametric statistical test used to determine if there are potential differences in the outcomes of three or more related groups on a binary (yes/no) or dichotomous outcome. It is essentially an extension of the McNemar Test, which is limited to two related samples - Cochran's Q test can handle three or more related samples, making it more versatile in scenarios where subjects are measured under multiple conditions. The test statistic follows a Chi-Square distribution,...
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...

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Related Experiment Video

Updated: Jun 7, 2026

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

A theory-based problem-solving approach to recruitment challenges in a large randomized field trial.

Susan Kossman1, Yichuan Hsieh, Jane Peace

  • 1Mennonite College of Nursing, Illinois State University, Normal, USA. skossm@ilstu.edu

Applied Nursing Research : ANR
|October 27, 2010
PubMed
Summary

Recruitment challenges in large field trials require adaptive problem-solving. A systematic approach enhanced participant accrual by identifying and addressing barriers continuously.

Related Experiment Videos

Last Updated: Jun 7, 2026

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

Area of Science:

  • Clinical Trials
  • Public Health Research
  • Biostatistics

Background:

  • Large field trials frequently encounter recruitment challenges, impacting study timelines and outcomes.
  • Sustaining participant accrual is critical for achieving target enrollment and statistical power.

Purpose of the Study:

  • To describe a systematic, theory-based problem-solving approach for addressing recruitment issues in large field trials.
  • To demonstrate how continuous strategy implementation can sustain participant accrual.

Main Methods:

  • A systematic, theory-based problem-solving framework was employed.
  • Research teams actively identified recruitment barriers and implemented adaptive strategies.
  • Continuous monitoring and adjustment of strategies were integral to the process.

Main Results:

  • The systematic approach facilitated a deeper understanding of recruitment challenges.
  • Continuous strategy implementation successfully sustained participant accrual towards the target enrollment.
  • Problem-solving enhanced the research team's ability to adapt and overcome obstacles.

Conclusions:

  • A structured, theory-based problem-solving methodology is effective for managing recruitment challenges in large field trials.
  • Adaptive strategies and continuous monitoring are essential for achieving and sustaining target enrollment in clinical research.