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Multivalued treatment, the Glossary

Index Multivalued treatment

In statistics, in particular in the design of experiments, a multi-valued treatment is a treatment that can take on more than two values.[1]

Table of Contents

  1. 3 relations: Causal inference, Design of experiments, Dose–response relationship.

  2. Experiments
  3. Quantitative research
  4. Statistical process control
  5. Statistical theory

Causal inference

Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system.

See Multivalued treatment and Causal inference

Design of experiments

The design of experiments (DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. Multivalued treatment and design of experiments are experiments, Industrial engineering, Quantitative research, Statistical process control, Statistical theory and systems engineering.

See Multivalued treatment and Design of experiments

Dose–response relationship

The dose–response relationship, or exposure–response relationship, describes the magnitude of the response of an organism, as a function of exposure (or doses) to a stimulus or stressor (usually a chemical) after a certain exposure time. Multivalued treatment and dose–response relationship are Pharmacodynamics and Toxicology.

See Multivalued treatment and Dose–response relationship

See also

Experiments

Quantitative research

Statistical process control

Statistical theory

References

[1] https://en.wikipedia.org/wiki/Multivalued_treatment

Also known as Multivalued treatments.