EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis
<p>Abstract</p> <p>This paper presents procedures for implementing the EM algorithm to compute REML estimates of variance covariance components in Gaussian mixed models for longitudinal data analysis. The class of models considered includes random coefficient factors, stationary ti...
| Main Authors: | , , |
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| Format: | Article |
| Language: | deu |
| Published: |
BMC
2000-03-01
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| Series: | Genetics Selection Evolution |
| Subjects: | |
| Online Access: | http://www.gsejournal.org/content/32/2/129 |
| _version_ | 1818808246205415424 |
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| author | Robert-Granié Christèle Jaffrézic Florence Foulley Jean-Louis |
| author_facet | Robert-Granié Christèle Jaffrézic Florence Foulley Jean-Louis |
| author_sort | Robert-Granié Christèle |
| collection | DOAJ |
| description | <p>Abstract</p> <p>This paper presents procedures for implementing the EM algorithm to compute REML estimates of variance covariance components in Gaussian mixed models for longitudinal data analysis. The class of models considered includes random coefficient factors, stationary time processes and measurement errors. The EM algorithm allows separation of the computations pertaining to parameters involved in the random coefficient factors from those pertaining to the time processes and errors. The procedures are illustrated with Pothoff and Roy's data example on growth measurements taken on 11 girls and 16 boys at four ages. Several variants and extensions are discussed.</p> |
| first_indexed | 2024-12-18T19:38:30Z |
| format | Article |
| id | doaj.art-48ea748480f841f3b630f6fa65ebcca3 |
| institution | Directory Open Access Journal |
| issn | 0999-193X 1297-9686 |
| language | deu |
| last_indexed | 2024-12-18T19:38:30Z |
| publishDate | 2000-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Genetics Selection Evolution |
| spelling | doaj.art-48ea748480f841f3b630f6fa65ebcca32022-12-21T20:55:31ZdeuBMCGenetics Selection Evolution0999-193X1297-96862000-03-0132212914110.1186/1297-9686-32-2-129EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysisRobert-Granié ChristèleJaffrézic FlorenceFoulley Jean-Louis<p>Abstract</p> <p>This paper presents procedures for implementing the EM algorithm to compute REML estimates of variance covariance components in Gaussian mixed models for longitudinal data analysis. The class of models considered includes random coefficient factors, stationary time processes and measurement errors. The EM algorithm allows separation of the computations pertaining to parameters involved in the random coefficient factors from those pertaining to the time processes and errors. The procedures are illustrated with Pothoff and Roy's data example on growth measurements taken on 11 girls and 16 boys at four ages. Several variants and extensions are discussed.</p>http://www.gsejournal.org/content/32/2/129EM algorithmREMLmixed modelsrandom regressionlongitudinal data |
| spellingShingle | Robert-Granié Christèle Jaffrézic Florence Foulley Jean-Louis EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis Genetics Selection Evolution EM algorithm REML mixed models random regression longitudinal data |
| title | EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis |
| title_full | EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis |
| title_fullStr | EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis |
| title_full_unstemmed | EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis |
| title_short | EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis |
| title_sort | em reml estimation of covariance parameters in gaussian mixed models for longitudinal data analysis |
| topic | EM algorithm REML mixed models random regression longitudinal data |
| url | http://www.gsejournal.org/content/32/2/129 |
| work_keys_str_mv | AT robertgraniechristele emremlestimationofcovarianceparametersingaussianmixedmodelsforlongitudinaldataanalysis AT jaffrezicflorence emremlestimationofcovarianceparametersingaussianmixedmodelsforlongitudinaldataanalysis AT foulleyjeanlouis emremlestimationofcovarianceparametersingaussianmixedmodelsforlongitudinaldataanalysis |