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Biological Age: Difference between revisions
→Estimation Methods
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Various methods have been developed to estimate BA, each with its unique approach and criteria:{{pmid|28546743}} | Various methods have been developed to estimate BA, each with its unique approach and criteria:{{pmid|28546743}} | ||
* '''Multiple Linear Regression (MLR)''' is a statistical technique that estimates BA by relating several independent variables (biomarkers) to a dependent variable (CA). In this method, CA is used as a criterion for selecting biomarkers and is treated as an independent index. | * '''Multiple Linear Regression (MLR)''' is a statistical technique that estimates BA by relating several independent variables (biomarkers) to a dependent variable (CA). In this method, CA is used as a criterion for selecting biomarkers and is treated as an independent index. | ||
* '''Principal Component Analysis (PCA)''' is another statistical technique used in BA estimation. PCA reduces the dimensionality of the data by transforming multiple biomarkers into a set of linearly uncorrelated variables, known as principal components. | * '''Principal Component Analysis (PCA)''' is another statistical technique used in BA estimation. PCA reduces the dimensionality of the data by transforming multiple biomarkers into a set of linearly uncorrelated variables, known as principal components. | ||
* '''Hochschild’s Method''' differs from MLR and PCA by making CA an independent variable. It aims to estimate BA by adjusting CA based on specific biomarkers. | * '''Hochschild’s Method''' differs from MLR and PCA by making CA an independent variable. It aims to estimate BA by adjusting CA based on specific biomarkers. | ||
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{| class="wikitable" | {| class="wikitable" | ||
! Method | ! Method | ||
! | ! Proposed | ||
! Core concept | ! Core concept | ||
! Advantage | ! Advantage | ||
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| MLR | | MLR | ||
| | | 1965{{pmid|5841151}} | ||
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| Aging biomarkers are determined by the correlation with CA using MLR model | | Aging biomarkers are determined by the correlation with CA using MLR model | ||
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| PCA | | PCA | ||
| Nakamura | | 1985, Nakamura | ||
| PCA uses fewer uncorrelated variables to explain the main variance | | PCA uses fewer uncorrelated variables to explain the main variance | ||
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| Hochschild’s method | | Hochschild’s method | ||
| Hochschild | | 1989, Hochschild | ||
| Hochschild’s method aims to select aging biomarkers according to their effects on life expectancy{{pmid|2684676}} | | Hochschild’s method aims to select aging biomarkers according to their effects on life expectancy{{pmid|2684676}} | ||
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| KDM | | KDM | ||
| Klemera and Doubal | | 2006, Klemera and Doubal | ||
| KDM is based on minimizing the distance between ''m'' regression lines and ''m'' biomarker points in an ''m''-dimensional space of all biomarkers{{pmid|16318865}} | | KDM is based on minimizing the distance between ''m'' regression lines and ''m'' biomarker points in an ''m''-dimensional space of all biomarkers{{pmid|16318865}} | ||
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