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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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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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Hazard Ratio01:12

Hazard Ratio

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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...
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures 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. Among the various sampling methods used by...
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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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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Randomized Trials Using Provincial Health Numbers for Group Assignment.

Amit X Garg1,2,3,4,5,6,7, Stephanie N Dixon1,2,3, Charlotte Ma1

  • 1ICES, Toronto, ON, Canada.

Canadian Journal of Kidney Health and Disease
|December 9, 2024
PubMed
Summary
This summary is machine-generated.

Provincial health card numbers in Ontario, Canada, can be used for individual-level randomization in large pragmatic trials. This method streamlines trial processes and reduces costs, but requires careful consideration of its impact on randomization integrity.

Keywords:
Ontario health cardadministrative health care datadialysispragmatic trialsrandomizationrandomized clinical trials

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Area of Science:

  • Health Services Research
  • Clinical Trials Methodology
  • Health Informatics

Background:

  • Provincial health card numbers in Ontario, Canada, are unique, lifelong identifiers assigned randomly.
  • These numbers are 10-digit strings with a version code, subject to proprietary alterations before assignment.
  • The random generation and unique nature of health card numbers present an opportunity for trial randomization.

Purpose of the Study:

  • To demonstrate the feasibility of using Ontario health card numbers for individual-level randomization in large pragmatic trials.
  • To analyze the distribution of health card digits for randomization purposes.
  • To discuss the practical and methodological considerations of this randomization approach.

Main Methods:

  • Analysis of health card number assignment and digit distribution in a trial setting.
  • Development of a randomization method utilizing specific digits of the health card number (e.g., the tenth digit).
  • Examination of the implications for trial integrity and stratification.

Main Results:

  • Health card numbers can be effectively used for individual-level randomization in large pragmatic trials.
  • The tenth digit of the Ontario health card number was utilized for randomization in a trial of dialysate bicarbonate concentrations.
  • The approach offers practical advantages, including streamlining processes and reducing trial costs.

Conclusions:

  • Using provincial health card numbers for pragmatic randomized trials is a viable strategy.
  • The benefits of this method, such as cost reduction and process streamlining, must be weighed against potential impacts on randomization integrity and stratification.
  • Careful consideration on a trial-by-trial basis is essential before implementing this approach.