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Variance Component


A variance component is a parameter representing the contribution of a random effect to the total variance in a statistical model. For the random-intercept model

 Y_(ij)=mu+A_i+epsilon_(ij),

with independent A_i and epsilon_(ij) having variances sigma_A^2 and sigma^2, respectively, the marginal variance of an observation is sigma_A^2+sigma^2. The two summands are variance components.

Observations sharing the same random effect are correlated. In the example, two observations in the same group have covariance sigma_A^2. Variance components are estimated in random effects models, often by maximizing an ordinary or restricted likelihood function.


See also

Covariance, Fixed Effects Model, Random Effects Model, Variance

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References

Searle, S. R.; Casella, G.; and McCulloch, C. E. Variance Components. Hoboken, NJ: Wiley, 2006.

Cite this as:

Weisstein, Eric W. "Variance Component." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/VarianceComponent.html

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