Testing Correlation in a Three-Level Model

Sammanfattning

In this paper, we present a statistical approach to evaluate the relationship between variables observed in a two-factors experiment. We consider a three-level model with covariance structure Sigma circle times psi(1) circle times psi(2), where Sigma is an arbitrary positive definite covariance matrix, and psi(1) and psi(2) are both correlation matrices with a compound symmetric structure corresponding to two different factors. The Rao's score test is used to test the hypotheses that observations grouped by one or two factors are uncorrelated. We analyze a fermentation process to illustrate the results.Supplementary materials accompanying this paper appear online.

Nyckelord

Three-level model; Rao's score test; Maximum likelihood estimation; Independence test; Factorial design; Kronecker product structured covariance matrix

Publicerad i

Journal of Agricultural, Biological, and Environmental Statistics
2024, volym: 29, nummer: 2, sidor: 257–276
Utgivare: SPRINGER

SLU författare

• von Rosen, Dietrich

  • Institutionen för energi och teknik, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Sannolikhetsteori och statistik

Publikationens identifierare

• DOI: https://doi.org/10.1007/s13253-023-00575-w

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/127701