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Beyond Multiple Linear Regression
Applied Generalized Linear Models And Multilevel Models in R
Buch von Paul Roback (u. a.)
Sprache: Englisch

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Beschreibung

For advanced undergraduate or non-major graduate students in Advanced Statistical Modeling or Regression II and courses in Generalized Linear Models, Longitudinal Data Analysis, Correlated Data, Multilevel Models. Material on R at the end of each chapter. Solutions manual for qualified instructors.

For advanced undergraduate or non-major graduate students in Advanced Statistical Modeling or Regression II and courses in Generalized Linear Models, Longitudinal Data Analysis, Correlated Data, Multilevel Models. Material on R at the end of each chapter. Solutions manual for qualified instructors.

Über den Autor

Authors

Paul Roback is the Kenneth O. Bjork Distinguished Professor of Statistics and Data Science and Julie Legler is Professor Emeritus of Statistics at St. Olaf College in Northfield, MN. Both are Fellows of the American Statistical Association and are founders of the Center for Interdisciplinary Research at St. Olaf. Dr. Roback is the past Chair of the ASA Section on Statistics and Data Science Education, conducts applied research using multilevel modeling, text analysis, and Bayesian methods, and has been a statistical consultant in the pharmaceutical, health care, and food processing industries. Dr. Legler is past Chair of the ASA/MAA Joint Committee on Undergraduate Statistics, is a co-author of Stat2: Modelling with Regression and ANOVA, and was a biostatistician at the National Cancer Institute.

Inhaltsverzeichnis
  1. Review of Multiple Linear Regression 2. Beyond Least Squares: Using Likelihoods to Fit and Compare Models 3. Distribution Theory 4. Poisson Regression 5. Generalized Linear Models (GLMs): A Unifying Theory 6. Logistic Regression 7. Correlated Data 8. Introduction to Multilevel Models 9. Two Level Longitudinal Data 10. Multilevel Data With More Than Two Levels 11. Multilevel Generalized Linear Models
Details
Erscheinungsjahr: 2020
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781439885383
ISBN-10: 1439885389
Sprache: Englisch
Einband: Gebunden
Autor: Roback, Paul
Legler, Julie
Hersteller: Taylor & Francis Ltd (Sales)
Maße: 241 x 162 x 32 mm
Von/Mit: Paul Roback (u. a.)
Erscheinungsdatum: 29.12.2020
Gewicht: 0,82 kg
Artikel-ID: 121216575
Über den Autor

Authors

Paul Roback is the Kenneth O. Bjork Distinguished Professor of Statistics and Data Science and Julie Legler is Professor Emeritus of Statistics at St. Olaf College in Northfield, MN. Both are Fellows of the American Statistical Association and are founders of the Center for Interdisciplinary Research at St. Olaf. Dr. Roback is the past Chair of the ASA Section on Statistics and Data Science Education, conducts applied research using multilevel modeling, text analysis, and Bayesian methods, and has been a statistical consultant in the pharmaceutical, health care, and food processing industries. Dr. Legler is past Chair of the ASA/MAA Joint Committee on Undergraduate Statistics, is a co-author of Stat2: Modelling with Regression and ANOVA, and was a biostatistician at the National Cancer Institute.

Inhaltsverzeichnis
  1. Review of Multiple Linear Regression 2. Beyond Least Squares: Using Likelihoods to Fit and Compare Models 3. Distribution Theory 4. Poisson Regression 5. Generalized Linear Models (GLMs): A Unifying Theory 6. Logistic Regression 7. Correlated Data 8. Introduction to Multilevel Models 9. Two Level Longitudinal Data 10. Multilevel Data With More Than Two Levels 11. Multilevel Generalized Linear Models
Details
Erscheinungsjahr: 2020
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781439885383
ISBN-10: 1439885389
Sprache: Englisch
Einband: Gebunden
Autor: Roback, Paul
Legler, Julie
Hersteller: Taylor & Francis Ltd (Sales)
Maße: 241 x 162 x 32 mm
Von/Mit: Paul Roback (u. a.)
Erscheinungsdatum: 29.12.2020
Gewicht: 0,82 kg
Artikel-ID: 121216575
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