Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing
Morphometric data usually have a hierarchical structure (i.e., cells are nested within patients), which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM), as well as corresponding software have receiv...
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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/10.1155/2003/506712 |
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| author | O. Tsybrovskyy A. Berghold |
| author_facet | O. Tsybrovskyy A. Berghold |
| author_sort | O. Tsybrovskyy |
| collection | DOAJ |
| description | Morphometric data usually have a hierarchical structure (i.e., cells are nested within patients), which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM), as well as corresponding software have received considerable development. However, there has been no application of these methods to morphometric data yet. In this paper we report our first experience of analyzing karyometric data by means of MLwiN – a dedicated program for multilevel modeling. Our data were obtained from 34 follicular adenomas and 44 follicular carcinomas of the thyroid. We show examples of fitting and interpreting MM of different complexity, and draw a number of interesting conclusions about the differences in nuclear morphology between follicular thyroid adenomas and carcinomas. We also demonstrate substantial advantages of multilevel models over conventional, single‐level statistics, which have been adopted previously to analyze karyometric data. In addition, some theoretical issues related to MM as well as major statistical software for MM are briefly reviewed. |
| format | Article |
| id | doaj-art-040e691840f04a5f8716ab6f38e6a948 |
| 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-040e691840f04a5f8716ab6f38e6a9482025-02-03T01:23:27ZengWileyAnalytical Cellular Pathology0921-89121878-36512003-01-0125417318510.1155/2003/506712Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis TestingO. Tsybrovskyy0A. Berghold1Department of Pathology, School of Medicine, University of Graz, AustriaInstitute for Medical Informatics, Statistics and Documentation, University of Graz, AustriaMorphometric data usually have a hierarchical structure (i.e., cells are nested within patients), which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM), as well as corresponding software have received considerable development. However, there has been no application of these methods to morphometric data yet. In this paper we report our first experience of analyzing karyometric data by means of MLwiN – a dedicated program for multilevel modeling. Our data were obtained from 34 follicular adenomas and 44 follicular carcinomas of the thyroid. We show examples of fitting and interpreting MM of different complexity, and draw a number of interesting conclusions about the differences in nuclear morphology between follicular thyroid adenomas and carcinomas. We also demonstrate substantial advantages of multilevel models over conventional, single‐level statistics, which have been adopted previously to analyze karyometric data. In addition, some theoretical issues related to MM as well as major statistical software for MM are briefly reviewed.http://dx.doi.org/10.1155/2003/506712 |
| spellingShingle | O. Tsybrovskyy A. Berghold Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing Analytical Cellular Pathology |
| title | Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing |
| title_full | Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing |
| title_fullStr | Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing |
| title_full_unstemmed | Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing |
| title_short | Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing |
| title_sort | application of multilevel models to morphometric data part 1 linear models and hypothesis testing |
| url | http://dx.doi.org/10.1155/2003/506712 |
| work_keys_str_mv | AT otsybrovskyy applicationofmultilevelmodelstomorphometricdatapart1linearmodelsandhypothesistesting AT aberghold applicationofmultilevelmodelstomorphometricdatapart1linearmodelsandhypothesistesting |