Confounding in the context of "Random assignment"

Behavioural genetics, also referred to as behaviour genetics, is a field of scientific research that uses genetic methods to investigate the nature and origins of individual differences in behaviour. While the name "behavioural genetics" connotes a focus on genetic influences, the field broadly investigates the extent to which genetic and environmental factors influence individual differences, and the development of research designs that can remove the confounding of genes and environment.

Behavioural genetics was founded as a scientific discipline by Francis Galton in the late 19th century, only to be discredited through association with eugenics movements before and during World War II. In the latter half of the 20th century, the field saw renewed prominence with research on inheritance of behaviour and mental illness in humans (typically using twin and family studies), as well as research on genetically informative model organisms through selective breeding and crosses. In the late 20th and early 21st centuries, technological advances in molecular genetics made it possible to measure and modify the genome directly. This led to major advances in model organism research (e.g., knockout mice) and in human studies (e.g., genome-wide association studies), leading to new scientific discoveries.

A pragmatic clinical trial (PCT), sometimes called a practical clinical trial (PCT), is a clinical trial that focuses on correlation between treatments and outcomes in real-world health system practice rather than focusing on proving causative explanations for outcomes, which requires extensive deconfounding with inclusion and exclusion criteria so strict that they risk rendering the trial results irrelevant to much of real-world practice.

A scientific control is an element of an experiment or observation designed to minimize the influence of variables other than the independent variable under investigation, thereby reducing the risk of confounding.

The use of controls increases the reliability and validity of results by providing a baseline for comparison between experimental measurements and control measurements. In many designs, the control group does not receive the experimental treatment, allowing researchers to isolate the effect of the independent variable.

In epidemiology, attributable fraction for the population (AFp) is the proportion of incidents in the population that are attributable to the risk factor. The term attributable risk percent for the population is used if the fraction is expressed as a percentage. It is calculated as ${\displaystyle AF_{p}=(I_{p}-I_{u})/I_{p}}$, where ${\displaystyle I_{p}}$ is the incidence in the population, and ${\displaystyle I_{u}}$ is the incidence in the unexposed group.

Equivalently it can be calculated as ${\displaystyle AF_{p}={\frac {P_{e}(RR-1)}{1+P_{e}(RR-1)}}}$, where ${\displaystyle P_{e}}$ is the exposed proportion of the population and ${\displaystyle RR}$ is the relative risk not adjusted for confounders.