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The covariance structure and likelihood function for multivariate dyadic data

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  • Li, Heng

Abstract

This paper extends the results in Li and Loken [A unified theory of statistical analysis and inference for variance component models for dyadic data, Statist. Sinica 12 (2002) 519-535] on the statistical analysis of measurements taken on dyads to the situations in which more than one attribute are measured on each dyad. Starting from the covariance structure for the univariate case obtained in Li and Loken (2002), the covariance structure for the multivariate case is derived based on the group symmetry induced by the assumed exchangeability in the units. Our primary objective is to document the Gaussian likelihood and the sufficient statistics for multivariate dyadic data in closed form, so that they can be referenced by researchers as they analyze those data. The derivation carried out can also serve as an example of multivariate extension of univariate models based on exchangeability.

Suggested Citation

  • Li, Heng, 2006. "The covariance structure and likelihood function for multivariate dyadic data," Journal of Multivariate Analysis, Elsevier, vol. 97(6), pages 1263-1271, July.
    • Handle: RePEc:eee:jmvana:v:97:y:2006:i:6:p:1263-1271
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    1. Li, Heng, 2002. "Likelihood-based quadratic analyses for diallel cross and other experiments involving data collected on ordered pairs of sampling units," Statistics & Probability Letters, Elsevier, vol. 58(1), pages 61-69, May.
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    Cited by:

    1. Steffen Nestler & Oliver Lüdtke & Alexander Robitzsch, 2020. "Maximum likelihood estimation of a social relations structural equation model," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 870-889, December.
    2. Steffen Nestler, 2018. "Likelihood Estimation of the Multivariate Social Relations Model," Journal of Educational and Behavioral Statistics, , vol. 43(4), pages 387-406, August.

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