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Primer of applied regression & analysis of variance / Stanton A. Glantz, Bryan K. Slinker, Torsten B. Neilands.

By: Contributor(s): Publication details: New York, New York : McGraw-Hill Education, 2016.Edition: Third editionDescription: xxvii, 1,183 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780071824118
  • 0071824111
Other title:
  • Primer of applied regression and analysis of variance
Subject(s): LOC classification:
  • QH 323.5 .G458 2016
  • QH323.5 .G56 2016
NLM classification:
  • WA 950
Online resources:
Contents:
Why do multivariate analysis? -- The first step : understanding simple linear regression -- Regression with two or more independent variables -- Do the data fit the assumptions? -- Multicollinearity and what to do about it -- Selecting the "best" regression model -- Missing data -- One-way analysis of variance -- Two-way analysis of variance -- Repeated measures -- Mixing continuous and categorical variables : analysis of covariance -- Regression with a qualitative dependent variable : logistic regression -- Regression modeling of time-to-event data : survival analysis -- Nonlinear regression
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Holdings
Item type Current library Call number Status Date due Barcode
Books Overnight Far Eastern University - Nicanor Reyes Medical Foundation Circulation Section QH 323.5 .G458 2016 (Browse shelf(Opens below)) Available 0009246

Includes bibliographical references and index.

Why do multivariate analysis? -- The first step : understanding simple linear regression -- Regression with two or more independent variables -- Do the data fit the assumptions? -- Multicollinearity and what to do about it -- Selecting the "best" regression model -- Missing data -- One-way analysis of variance -- Two-way analysis of variance -- Repeated measures -- Mixing continuous and categorical variables : analysis of covariance -- Regression with a qualitative dependent variable : logistic regression -- Regression modeling of time-to-event data : survival analysis -- Nonlinear regression

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