Additive model

From WikiMD.org
Jump to navigation Jump to search

Additive Model

The Additive Model (pronunciation: /ædˈɪtɪv ˈmɒdəl/) is a statistical linear model used in various fields, including medicine, biology, and genetics. It is a type of statistical model that is used to predict the outcome of a response variable based on the sum of the effects of the individual variables.

Etymology

The term "additive model" comes from the mathematical concept of addition, referring to the way the model adds together the effects of each variable to predict the outcome.

Definition

In an additive model, the effect of each variable on the outcome is considered to be additive, meaning that the effect of each variable is independent of the effects of the other variables. This is in contrast to a multiplicative model, where the effect of each variable can depend on the levels of the other variables.

Usage in Medicine

In medicine, additive models are often used in epidemiology to study the effects of multiple risk factors on a disease outcome. For example, an additive model might be used to study the combined effects of age, gender, and smoking status on the risk of developing lung cancer.

Related Terms

External links

Esculaap.svg

This WikiMD dictionary article is a stub. You can help make it a full article.


Languages: - East Asian 中文, 日本, 한국어, South Asian हिन्दी, Urdu, বাংলা, తెలుగు, தமிழ், ಕನ್ನಡ,
Southeast Asian Indonesian, Vietnamese, Thai, မြန်မာဘာသာ, European español, Deutsch, français, русский, português do Brasil, Italian, polski