Application of Multilevel Models to Morphometric Data. Part 2. Correlations
Multilevel organization of morphometric data (cells are “nested” within patients) requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance) matrices are produced for every level in the hierarc...
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| Format: | Article |
| Language: | English |
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Wiley
2003-01-01
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| Series: | Analytical Cellular Pathology |
| Online Access: | http://dx.doi.org/10.1155/2003/562508 |
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| author | O. Tsybrovskyy A. Berghold |
| author_facet | O. Tsybrovskyy A. Berghold |
| author_sort | O. Tsybrovskyy |
| collection | DOAJ |
| description | Multilevel organization of morphometric data (cells are “nested” within patients) requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance) matrices are produced for every level in the hierarchy. In karyometric research, the cell‐level (i.e., within‐tumor) correlations seem to be of major interest. Beside their biological importance, these correlation coefficients (CC) are compulsory when dimensionality reduction is required. Using MLwiN, a dedicated program for multilevel modeling, we show how to use multivariate multilevel models (MMM) to obtain and interpret CC in each of the levels. A comparison with two usual, “single‐level” statistics shows that MMM represent the only way to obtain correct cell‐level correlation coefficients. The summary statistics method (take average values across each patient) produces patient‐level CC only, and the “pooling” method (merge all cells together and ignore patients as units of analysis) yields incorrect CC at all. We conclude that multilevel modeling is an indispensable tool for studying correlations between morphometric variables. |
| format | Article |
| id | doaj-art-30551c55c327459caff06b75714414a9 |
| institution | Kabale University |
| issn | 0921-8912 1878-3651 |
| language | English |
| publishDate | 2003-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Analytical Cellular Pathology |
| spelling | doaj-art-30551c55c327459caff06b75714414a92025-02-03T01:03:46ZengWileyAnalytical Cellular Pathology0921-89121878-36512003-01-0125418719110.1155/2003/562508Application of Multilevel Models to Morphometric Data. Part 2. CorrelationsO. Tsybrovskyy0A. Berghold1Department of Pathology, School of Medicine, University of Graz, AustriaInstitute for Medical Informatics, Statistics and Documentation, University of Graz, AustriaMultilevel organization of morphometric data (cells are “nested” within patients) requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance) matrices are produced for every level in the hierarchy. In karyometric research, the cell‐level (i.e., within‐tumor) correlations seem to be of major interest. Beside their biological importance, these correlation coefficients (CC) are compulsory when dimensionality reduction is required. Using MLwiN, a dedicated program for multilevel modeling, we show how to use multivariate multilevel models (MMM) to obtain and interpret CC in each of the levels. A comparison with two usual, “single‐level” statistics shows that MMM represent the only way to obtain correct cell‐level correlation coefficients. The summary statistics method (take average values across each patient) produces patient‐level CC only, and the “pooling” method (merge all cells together and ignore patients as units of analysis) yields incorrect CC at all. We conclude that multilevel modeling is an indispensable tool for studying correlations between morphometric variables.http://dx.doi.org/10.1155/2003/562508 |
| spellingShingle | O. Tsybrovskyy A. Berghold Application of Multilevel Models to Morphometric Data. Part 2. Correlations Analytical Cellular Pathology |
| title | Application of Multilevel Models to Morphometric Data. Part 2. Correlations |
| title_full | Application of Multilevel Models to Morphometric Data. Part 2. Correlations |
| title_fullStr | Application of Multilevel Models to Morphometric Data. Part 2. Correlations |
| title_full_unstemmed | Application of Multilevel Models to Morphometric Data. Part 2. Correlations |
| title_short | Application of Multilevel Models to Morphometric Data. Part 2. Correlations |
| title_sort | application of multilevel models to morphometric data part 2 correlations |
| url | http://dx.doi.org/10.1155/2003/562508 |
| work_keys_str_mv | AT otsybrovskyy applicationofmultilevelmodelstomorphometricdatapart2correlations AT aberghold applicationofmultilevelmodelstomorphometricdatapart2correlations |