randomization model - определение. Что такое randomization model
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Что (кто) такое randomization model - определение

STATISTICAL METHOD IN GENETIC EPIDEMIOLOGY
Mendelian randomisation; Mendelian randomization analysis; Mendelian Randomization
  • Directed acyclic graph traditionally used to represent the Mendelian randomization framework and its core assumptions. <math>Z</math> is the genetic variants, <math>X</math> is the exposure, <math>Y</math> is the outcome of interest, and <math>U</math> are possible confounders.
  • Gregor Mendel. The term Mendelian randomization was termed because the random assignment of genetic variants from parents to offspring is fundamental to the method.

Mendelian randomization         
In epidemiology, Mendelian randomization (commonly abbreviated to MR) is a method using measured variation in genes to interrogate the causal effect of an exposure on an outcome. Under key assumptions (see below), the design reduces both reverse causation and confounding, which often substantially impede or mislead the interpretation of results from epidemiological studies.
Random surfing model         
GRAPH MODEL OF WEB PAGES SIMILAR TO MARKOV CHAINS
Draft:Random Surfing Model; Random Surfing Model
The random surfing model is a graph model which describes the probability of a random user visiting a web page. The model attempts to predict the chance that a random internet surfer will arrive at a page by either clicking a link or by accessing the site directly, for example by directly entering the website's URL in the address bar.
Random waypoint model         
Random direction model
In mobility management, the random waypoint model is a random model for the movement of mobile users, and how their location, velocity and acceleration change over time. Mobility models are used for simulation purposes when new network protocols are evaluated.

Википедия

Mendelian randomization

In epidemiology, Mendelian randomization (commonly abbreviated to MR) is a method using measured variation in genes to interrogate the causal effect of an exposure on an outcome. Under key assumptions (see below), the design reduces both reverse causation and confounding, which often substantially impede or mislead the interpretation of results from epidemiological studies.

The study design was first proposed in 1986 and subsequently described by Gray and Wheatley as a method for obtaining unbiased estimates of the effects of a putative causal variable without conducting a traditional randomized controlled trial (i.e. the "gold standard" in epidemiology for establishing causality). These authors also coined the term Mendelian randomization.