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Related Concept Videos

Systematic Sampling Method01:17

Systematic 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.
Systematic sampling is one of the simplest methods...
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Sampling Plans01:23

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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.
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Convenience Sampling Method00:55

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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.
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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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Stratified Sampling Method01:16

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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.
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Sampling Methods: Overview01:06

Sampling Methods: Overview

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
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Infinium Assay for Large-scale SNP Genotyping Applications
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A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

James H Boyd1, Tenniel Guiver, Sean M Randall

  • 1James H. Boyd, Centre for Population Health Research, Faculty of Health Sciences, Curtin University, Bentley 6102 WA, Australia,

Methods of Information in Medicine
|April 21, 2016
PubMed
Summary

This study introduces a sampling method to accurately estimate record linkage quality, including precision and recall. The approach is crucial for large-scale population studies with millions of record pairs.

Keywords:
Medical record linkageelectronic health recordsestimationlinkage qualitysampling

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Area of Science:

  • Health Informatics
  • Data Science
  • Biostatistics

Background:

  • Record linkage integrates diverse datasets for comprehensive health status assessment.
  • High linkage quality is essential for research integrity.
  • Current methods struggle to measure false negatives, impacting quality assessment.

Purpose of the Study:

  • To introduce and evaluate a novel sampling-based method for estimating both precision and recall in record linkage.
  • To address limitations in current record linkage quality assessment methods.

Main Methods:

  • A sampling strategy involving clerical review of record-pairs across all thresholds was employed.
  • Estimates of false positives and false negatives were derived from sampled data.
  • The method's efficacy was validated using a synthetic dataset with known true match statuses.

Main Results:

  • Sampled estimates of linkage quality closely approximated true metrics on the synthetic dataset.
  • High consistency was observed among seven reviewers, with a Fleiss Kappa of 0.601.
  • The sampling method accurately estimated precision and recall.

Conclusions:

  • The proposed sampling method offers a viable approach for accurate matching quality estimation in large-scale population linkage studies.
  • This method is particularly valuable for projects involving millions of record pairs.
  • It facilitates the refinement of linkages in population health research.