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Related Concept Videos

Longitudinal Studies01:26

Longitudinal Studies

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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Fisher's Exact Test01:08

Fisher's Exact Test

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Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
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Variance01:15

Variance

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The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the data....
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Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

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Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
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Components of Stress01:23

Components of Stress

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Stress analysis under multiple loading conditions is intricate, necessitating a comprehensive grasp of normal and shearing stresses. Consider a small cube at point O, subjected to stress on all six faces, visible or not. Normal stress components σx, σy, σz act perpendicularly to the x, y, and z axes. Shearing stress components τxy and τxz are exerted on faces perpendicular to these axes.
Interestingly, the hidden cube faces also experience these stresses, equal and...
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Pulse Wave Velocity Testing in the Baltimore Longitudinal Study of Aging
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Exact variance component tests for longitudinal microbiome studies.

Jing Zhai1, Kenneth Knox2, Homer L Twigg3

  • 1Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona.

Genetic Epidemiology
|January 10, 2019
PubMed
Summary
This summary is machine-generated.

We developed new statistical tests for analyzing longitudinal microbiome data in human immunodeficiency virus (HIV) studies. Our method accurately identifies associations between lung microbiome composition and clinical outcomes, even with small sample sizes.

Keywords:
human immunodeficiency viruslinear mixed effects modelslongitudinal pulmonary microbiomevariance component models

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Area of Science:

  • Microbiome research
  • Statistical genetics
  • Computational biology

Background:

  • Metagenomic studies often test associations between microbiome composition and clinical outcomes.
  • Current statistical methods for microbiome analysis are limited to two variance components and large sample sizes, restricting their application to longitudinal microbiome data.
  • Longitudinal microbiome studies are crucial for understanding dynamic changes in microbial communities over time, particularly in the context of chronic diseases like HIV.

Purpose of the Study:

  • To propose novel exact statistical tests for analyzing longitudinal microbiome data with multiple variance components.
  • To address the limitations of existing methods that are not applicable to complex longitudinal microbiome studies.
  • To identify specific microbiome clusters associated with clinical outcomes while accounting for related effects.

Main Methods:

  • Development of exact tests (score test, likelihood ratio test, restricted likelihood ratio test) for variance component models with more than two components.
  • A strategy to reduce multiple variance components to a single component for hypothesis testing.
  • Application of the proposed methods to longitudinal pulmonary microbiome data from human immunodeficiency virus (HIV)-infected patients.

Main Results:

  • The proposed method demonstrates correct type I error rates in simulation studies.
  • The new approach shows superior statistical power compared to existing methods, especially for small sample sizes and weak signals.
  • Analysis of HIV-infected patients' lung microbiome revealed associations between Prevotella and Veillonella genera and forced vital capacity.

Conclusions:

  • The developed statistical framework provides an effective tool for analyzing longitudinal microbiome data in complex study designs.
  • The findings highlight the significant impact of the lung microbiome on HIV-related pulmonary complications.
  • The open-source implementation in Julia facilitates wider adoption and application in microbiome research.