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Linear mixed-effects models using R : a step-by-step approach / Andrzej Ga士i, Tomasz Burzykowski.

By: Contributor(s): Series: pringer texts in statisticsPublication details: New York, NY : Springer, c2013.Description: 542 p. : ill. ; 24 cmISBN:
  • 9781461438991 (alk. paper)
  • 1461438993 (alk. paper)
Subject(s):
Contents:
Introduction -- Introduction -- Case Studies -- Data Exploration -- Linear Models for Independent Observations -- Linear Models with Homogeneous Variance -- Fitting Linear Models with Homogeneous Variance: The lm() and gls() Functions -- ARMD Trial: Linear Model with Homogeneous Variance -- Linear Models with Heterogeneous Variance -- Fitting Linear Models with Heterogeneous Variance: The gls() Function -- ARMD Trial: Linear Model with Heterogeneous Variance -- Linear Fixed-effects Models for Correlated Data -- Linear Model with Fixed Effects and Correlated Errors -- Fitting Linear Models with Fixed Effects and Correlated Errors: The gls() Function -- ARMD Trial: Modeling Correlated Errors for Visual Acuity -- Linear Mixed-effects Models -- Linear Mixed-Effects Model -- Fitting Linear Mixed-Effects Models: The lme()Function -- Fitting Linear Mixed-Effects Models: The lmer() Function -- ARMD Trial: Modeling Visual Acuity -- PRT Trial: Modeling Muscle Fiber Specific-Force -- SII Project: Modeling Gains in Mathematics Achievement-Scores -- FCAT Study: Modeling Attainment-Target Scores -- Extensions of the RTools for Linear Mixed-Effects Models.
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Item type Current library Home library Collection Call number Materials specified Copy number Status Date due Barcode
AM PERPUSTAKAAN TUN SERI LANANG PERPUSTAKAAN TUN SERI LANANG KOLEKSI AM-P. TUN SERI LANANG (ARAS 5) - QA279.G343 (Browse shelf(Opens below)) 1 Available 00002106681

Includes bibliographical references and indexes.

Introduction -- Introduction -- Case Studies -- Data Exploration -- Linear Models for Independent Observations -- Linear Models with Homogeneous Variance -- Fitting Linear Models with Homogeneous Variance: The lm() and gls() Functions -- ARMD Trial: Linear Model with Homogeneous Variance -- Linear Models with Heterogeneous Variance -- Fitting Linear Models with Heterogeneous Variance: The gls() Function -- ARMD Trial: Linear Model with Heterogeneous Variance -- Linear Fixed-effects Models for Correlated Data -- Linear Model with Fixed Effects and Correlated Errors -- Fitting Linear Models with Fixed Effects and Correlated Errors: The gls() Function -- ARMD Trial: Modeling Correlated Errors for Visual Acuity -- Linear Mixed-effects Models -- Linear Mixed-Effects Model -- Fitting Linear Mixed-Effects Models: The lme()Function -- Fitting Linear Mixed-Effects Models: The lmer() Function -- ARMD Trial: Modeling Visual Acuity -- PRT Trial: Modeling Muscle Fiber Specific-Force -- SII Project: Modeling Gains in Mathematics Achievement-Scores -- FCAT Study: Modeling Attainment-Target Scores -- Extensions of the RTools for Linear Mixed-Effects Models.

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