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Randomized Experiments

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...

Law of Independent Assortment

Law of Independent Assortment

While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.

Dihybrid Crosses

Dihybrid Crosses

Law of Segregation

Law of Segregation

When crossing pea plants, Mendel noticed that one of the parental traits would sometimes disappear in the first generation of offspring, called the F1 generation, and could reappear in the next generation (F2). He concluded that one of the traits must be dominant over the other, thereby causing masking of one trait in the F1 generation. When he crossed the F1 plants, he found that 75% of the offspring in the F2 generation had the dominant phenotype, while 25% had the recessive phenotype.

Monohybrid Crosses

Monohybrid Crosses

Chromosomal Theory of Inheritance

Chromosomal Theory of Inheritance

In 1866, Gregor Mendel published the results of his pea plant breeding experiments, providing evidence for predictable patterns in the inheritance of physical characteristics. The significance of his findings was not immediately recognized. In fact, the existence of genes was unknown at the time. Mendel referred to hereditary units as “factors.”

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Related Experiment Video

Updated: Jul 26, 2025

Gene-targeted Random Mutagenesis to Select Heterochromatin-destabilizing Proteasome Mutants in Fission Yeast

Gene-targeted Random Mutagenesis to Select Heterochromatin-destabilizing Proteasome Mutants in Fission Yeast

Published on: May 15, 2018

Mendelian randomization.

Eleanor Sanderson^1,2, M Maria Glymour³, Michael V Holmes^1,4,5

¹Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Nature Reviews. Methods Primers

|June 16, 2023

Summary

This summary is machine-generated.

Mendelian randomization (MR) uses genetic variations to determine causal links between exposures and outcomes, overcoming confounding factors. This primer explains MR principles, methods, assumption checks, and its role in evidence triangulation for causal inference.

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Area of Science:

Epidemiology
Genetics
Biostatistics

Background:

Causal inference in observational studies is challenged by unobserved confounding.
Mendelian randomization (MR) offers a genetic approach to address these challenges.

Purpose of the Study:

To outline the fundamental principles of Mendelian randomization (MR).
To explain the instrumental variable conditions essential for MR estimation.
To discuss methods for assessing MR assumptions and robust estimation techniques.

Main Methods:

Leveraging genetic variants as instrumental variables.
Applying instrumental variable estimation techniques.
Assessing the validity of MR assumptions.

Main Results:

MR enables causal effect inference by mitigating unobserved confounding.
Methods are presented for robust estimation even with assumption violations.
Examples illustrate MR's application across diverse studies.

Conclusions:

MR provides a powerful tool for causal inference in epidemiology.
It complements other epidemiological methods through evidence triangulation.
Understanding MR assumptions is crucial for reliable causal conclusions.