{"product_id":"9783031722462","title":"Application of Regularized Regressions to Identify Novel Predictors in Clinical Research","description":"\u003ch1\u003eApplication of Regularized Regressions to Identify Novel Predictors in Clinical Research\u003c\/h1\u003e \u003ch2\u003eCleophas, Ton J.; Zwinderman, Aeilko H.\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis textbook is an important novel menu for multiple variables regression entitled \"regularized regression\". It is a must have for identifying unidentified leading factors. Also, you get fitted parameters for your overfitted data. Finally, there is no more need for commonly misunderstood p-values. Instead, the regression coefficient, R-value, as reported from a regression line has been applied as the key predictive estimator of the regression study. With simple one by one variable regression it is no wider than -1 to +1. With multiple variables regression it can easily get \u0026gt; +1 or \u0026lt; -1. This means we have a seriously flawed regression model, mostly due to collinearity or non-linear data. Completing the analysis will lead to overfitting, and thus a meaningless significant study due to data spread wider than compatible with random. In order for the regression coefficients to remain in the right size, fortunately a shrinking procedure has been invented.\u003c\/p\u003e\n\n\u003cp\u003eIn the past two decades regularized regression has become a major topic of research, particularly with high dimensional data. Yet, the method is pretty new and infrequently used in real-data analysis. Its performance as compared to traditional null hypothesis testing has to be confirmed by prospective comparisons. Most studies published to date are of a theoretical nature involving statistical modeling and simulation studies. The journals Nature and Science published 19 and 10 papers of this sort in the past 8 years. The current edition will for the first time systematically test regularized regression against traditional regression analysis in 20 clinical data examples.\u003c\/p\u003e\n\n\u003cp\u003eThe edition is also a textbook and tutorial for medical and healthcare students as well as recollection bench and help desk for professionals. Each chapter can be studied as a standalone, and, using, real as well as hypothesized data, it tests the performance of the novel methodology against traditional regressions. Step by step analyses of 20 data files are included for self-assessment. The authors are well qualified in their field. Professor Zwinderman is past-president of the International Society of Biostatistics and Professor Cleophas is past-president of the American College of Angiology. The authors have been working together for 25 years and their research can be characterized as a continued effort to demonstrate that clinical data analysis is a discipline at the interface of biology and mathematics.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2024-12-21\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783031722462\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-031-72247-9\u003c\/p\u003e \u003cp\u003eDimensions: 235.0cm x155.0cm\u003c\/p\u003e \u003cp\u003ePages: 273.0\u003c\/p\u003e ","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":45549631275148,"sku":"9783031722462","price":152.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783031722462.jpg?v=1766474649","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783031722462","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}