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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...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
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...
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...
Study Design in Statistics01:15

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.

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Related Experiment Video

Updated: Jun 6, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Data sharing in stepped-wedge cluster randomized trials: suboptimal data availability despite "data available upon

Cory E Goldstein1, Anna Catharina V Armond2, Kelly D Cobey2

  • 1Methodological and Implementation Research Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa Ontario, Canada.

Journal of Clinical Epidemiology
|June 4, 2026
PubMed
Summary
This summary is machine-generated.

Data sharing statements in stepped-wedge cluster randomized trials (SW-CRTs) do not guarantee data access. Actual data obtainment rates are low, with regional variations influencing success, highlighting a need for better data sharing guidance.

Keywords:
Cluster randomized trialsData availabilityData sharingOpen dataReproducibilityResearch transparencyStatistical methodsStepped-wedge trials

Related Experiment Videos

Last Updated: Jun 6, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Health Research Methodology
  • Biostatistics
  • Clinical Trials

Background:

  • Data sharing is crucial for research transparency, reproducibility, and innovation.
  • Access to real-world trial data is essential for statistical method development and validation.

Purpose of the Study:

  • To assess the prevalence and types of data sharing statements in published stepped-wedge cluster randomized trials (SW-CRTs).
  • To determine the actual availability of SW-CRT datasets upon author request.
  • To identify factors associated with successful data obtainment.

Main Methods:

  • Identified SW-CRTs published between 2016-2023.
  • Classified data sharing statements (publicly available, available upon request, not available).
  • Emailed authors to request datasets and analyzed factors associated with data obtainment using logistic regression.

Main Results:

  • Only 45% of SW-CRTs had clear data sharing statements; 35% of datasets were obtained.
  • Data obtainment rates did not differ between studies with no statement and those available upon request.
  • Trials in low- and middle-income countries showed higher odds of data obtainment (OR=2.9).

Conclusions:

  • Data sharing practices in SW-CRTs are suboptimal, with statements not reflecting actual data availability.
  • Regional variations significantly impact data obtainment, while other trial characteristics have limited influence.
  • Improved guidance and resources are necessary to facilitate effective data sharing in health research.