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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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
Simple...
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

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 from...
What is an Experiment?01:12

What is an Experiment?

An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Experimental Designs01:16

Experimental Designs

An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...

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Related Experiment Videos

Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions.

M Maria Glymour1, Eric J Tchetgen Tchetgen, James M Robins

  • 1Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. mglymour@hsph.harvard.edu

American Journal of Epidemiology
|January 17, 2012
PubMed
Summary

Mendelian randomization (MR) studies require rigorous assumption checks for reliable results. This study introduces methods to validate MR analyses, enhancing the credibility of genetic and observational research.

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Area of Science:

  • Epidemiology
  • Genetics
  • Biostatistics

Background:

  • Mendelian randomization (MR) studies, a type of instrumental variable (IV) analysis, rely on strong assumptions.
  • These assumptions are often not systematically evaluated in MR applications, potentially impacting study credibility.

Purpose of the Study:

  • To present methods for systematically evaluating the validity of MR studies.
  • To apply these methods to an MR study investigating the effect of obesity on mental disorder using FTO genotype as an IV.
  • To describe the assumptions underlying these IV assessment methods.

Main Methods:

  • The authors detail several methods for assessing the validity of instrumental variable assumptions in MR studies.
  • These methods were applied to a specific MR study examining the relationship between obesity and mental disorder.
  • The assessment techniques are applicable to any IV analysis, including those using genetic or other sources of exogenous variation.

Main Results:

  • The presented methods can help evaluate the validity of MR studies, though they are not infallible.
  • The application to an FTO-based MR study demonstrated the utility of these assessment techniques.
  • The evaluation approaches may sometimes fail to detect biased IVs or incorrectly flag valid IVs as biased.

Conclusions:

  • Routinely applying methods to assess MR assumptions is crucial for improving the scientific rigor and contributions of MR studies.
  • While not conclusive, these assessment methods enhance the credibility of IV analyses.
  • The described techniques are broadly relevant for any instrumental variable analysis.