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Related Concept Videos

Stratified Sampling Method01:16

Stratified Sampling Method

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...
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...
Sampling Plans01:23

Sampling Plans

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...
Cluster Sampling Method01:20

Cluster Sampling Method

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...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Systematic Sampling Method01:17

Systematic Sampling Method

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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Methods for detecting and correcting for population stratification.

Todd L Edwards1, Xiaoyi Gao

  • 1Center for Human Genetics Research, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA.

Current Protocols in Human Genetics
|April 4, 2012
PubMed
Summary
This summary is machine-generated.

Population stratification (PS) can confound genetic studies. This review covers methods to detect and correct for PS in human populations, ensuring reliable genetic association findings.

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Methodology for Accurate Detection of Mitochondrial DNA Methylation
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Area of Science:

  • Genetics
  • Population Genetics
  • Bioinformatics

Background:

  • Population stratification (PS) is a critical factor in human genetic studies.
  • Ignoring PS can lead to spurious associations or failed studies due to confounding.
  • This issue is particularly relevant for minority populations where PS is common.

Purpose of the Study:

  • To review historical and current methods for addressing population stratification in genetic association studies.
  • To highlight the importance of controlling for PS in human population research.

Main Methods:

  • Review of established and novel techniques for detecting PS, including global and local ancestry inference.
  • Description of statistical approaches to adjust association statistics for confounding effects of PS.

Main Results:

  • Identified various methods for PS detection and correction.
  • Emphasized the necessity of these methods for accurate genetic association analysis.

Conclusions:

  • Effective control of population stratification is essential for valid genetic studies.
  • Implementing these methods ensures the integrity of genetic association findings, especially in diverse populations.