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008			210301s2021 gw a o |||| 0|eng d
020			_a9783030613945
024	7		_a10.1007/978-3-030-61394-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQH323.5 _b2021 EB
100	1		_aCleophas, Ton J. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _986087
245	1	0	_aRegression analysis in medical research : _bfor Starters and 2nd Levelers _cby Ton J Cleophas, Aeilko H Zwinderman
250			_aSecond edition 2021
264		1	_aCham, Switzerland _bSpringer International Publising _c2021
300			_a1 recurso en línea (XV, 475 páginas) _b482 ilustraciones, 72 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
505	0		_aPreface -- Continuous Outcome Regressions -- Dichotomous Outcome Regressions -- Confirmative Regressions -- Dichotomous Regressions Other than Logistic and Cox -- Polytomous Outcome Regressions -- Time to Event Regressions other than Traditional Cox -- Analysis of Variance (ANOVA) -- Repeated Outcomes Regression Methods -- Methodologies for Better Fit of Categorical Predictors -- Laplace Regressions, Multi- instead of Mono-Exponential Models -- Regressions For Making Extrapolations. -- Standardized Regression Coefficients -- Multivariate Analysis of Variance and Canonical Regression -- More on Poisson Regressions -- Regression Trend Testing -- Optimal Scaling and Automatic Linear Regression -- Spline Regressions -- More on Nonlinear Regressions -- Special Forms of Continuous Outcome Regressions -- Regressions for Quantitative Diagnostic Testing -- Regressions, a Panacee or at Least a Widespread Help for Data Analyses -- Regression Trees -- Regressions with Latent Variables -- Partial Correlations -- Functional Data Analysis Basis -- Functional Data Analysis Advanced -- Quantile Regression -- Index. .
520	3		_aRegression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals. It came to the authors' attention, that information of history, background, and purposes, of the regression methods addressed were scanty. Lacking information about all of that has now been entirely covered. The editorial art work of the first edition, however pretty, was less appreciated by some readerships, than were the original output sheets from the statistical programs as used. Therefore, the editorial art work has now been systematically replaced with original statistical software tables and graphs for the benefit of an improved usage and understanding of the methods. In the past few years, professionals have been flooded with big data. The Covid-19 pandemic gave cause for statistical software companies to foster novel analytic programs better accounting outliers and skewness. Novel fields of regression analysis adequate for such data, like sparse canonical regressions and quantile regressions, have been included.
988			_aSpringer_Computer_2021
650		7	_2embne _9139105 _aBiometría
650		7	_2embne _9143128 _aAnálisis de regresión
700	1		_aZwinderman, Aeilko H. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _986088
710	2		_aSpringerLink
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-61394-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2021 _dz _eb _zSI