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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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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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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Stratified Sampling Method01:16

Stratified 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. 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.
To choose a stratified sample, divide the population into groups called strata and then take a...
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How to do random allocation (randomization).

Jeehyoung Kim1, Wonshik Shin1

  • 1Department of Orthopedic Surgery, Seoul Sacred Heart General Hospital, Seoul, Korea.

Clinics in Orthopedic Surgery
|March 8, 2014
PubMed
Summary
This summary is machine-generated.

Random allocation is crucial for unbiased randomized controlled studies. This guide explains its concept, easy execution, and reporting for robust clinical trial design.

Keywords:
Block randomizationRandom allocationSimple randomizationStratified randomization

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Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Research Design

Background:

  • Randomized controlled trials (RCTs) are the gold standard for evaluating interventions.
  • Ensuring unbiased comparison between treatment groups is paramount in RCTs.
  • Random allocation is a fundamental technique for achieving allocation concealment.

Purpose of the Study:

  • To elucidate the core principles of random allocation in research.
  • To provide a practical guide for implementing random allocation procedures.
  • To outline best practices for reporting random allocation in scientific publications.

Main Methods:

  • Explanation of the concept of random allocation.
  • Demonstration of simple methods for performing random allocation.
  • Guidance on transparently reporting the random allocation process.

Main Results:

  • Understanding random allocation enhances study validity.
  • Simple methods facilitate easy implementation of random allocation.
  • Clear reporting of random allocation improves research reproducibility.

Conclusions:

  • Random allocation is essential for minimizing bias in RCTs.
  • Accessible methods empower researchers to implement this technique effectively.
  • Standardized reporting of random allocation strengthens the integrity of scientific evidence.