Regression Analysis

{
  "id": "MLC-T-ENV-023620",
  "term": "Regression Analysis",
  "field": "Environment",
  "definition": "1. Analysis of the functional relationship between two variables; the independent variable is described on the X axis and the dependent variable is described on the Y axis (i.e. the change in Y is a function of a change in X).\n\n2. A method for determining the association between a dependent variable and one or more independent variables.\n\n3. A statistical process that produces a mathematical function (regression equation) that relates a dependent variable (biological effect) to independent variable, e.g., dose rate, duration of exposure, age.\n\n4. Mathematical technique that estimates the statistical relationships between dependent and independent variables.\n\n5. Regression analysis provides a \"best-fit\" mathematical equation for the relationship between the dependent variable (response) and independent variable(s) (covariates). There are two major classes of regression - parametric and non-parametric. Parametric regression requires choice of the regression equation with one or a greater number of unknown parameters. Linear regression, in which a linear relationship between the dependent variable and independent variables is posited, is an example. The aim of parametric regression is to find the values of these parameters which provide the best fit to the data. The number of parameters is usually much smaller than the number of data points. In contrast, the non-parametric regression requires no such a choice of the regression equation.\n\n6. Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression the relationship is constrained to be a straight line and least-squares analysis is used to determine the best fit. In logistic regression the dependent variable is qualitative rather than continuously variable and likelihood functions are used to find the best relationship. In multiple regression the dependent variable is considered to depend on more than a single independent variable. [CancerWeb 2005]\n\n7. The analysis of the relationship between a dependent variable and one or more independent variables. Its purpose is to determine whether a relationship exists and the strength of the relationship. It is also used to determine the mathematical relationship between the variables, predict the values of the dependent variable and control other independent variables when evaluating the effect of one or more independent variables. [ESOMAR 2001]\n\n8. Statistical process that produces a mathematical function (regression equation) that relates a dependent variable (biological effect) to independent variable, e.g., dose rate, duration of exposure, age. [Benchmark Dose Software (BMDS) Glossary of Terms]",
  "subject": "Chemicals, toxics and pesticides",
  "references": [
    "Waste and Cleanup Risk Assessment Glossary",
    "Program Evaluation Glossary",
    "Benchmark Dose Software (BMDS) Glossary of Terms; N-STEPS Online Glossary of Terms",
    "Thurston",
    "National Cancer Institute Thesaurus",
    "Thesaurus of Terms Used in Microbial Risk Assessment",
    "NSTEPS Online Glossary of Terms"
  ],
  "url": "https://mlchart.com/terminology/environment/regression-analysis/"
}