05.04.2023 Views

Download⚡️ Analysis of Longitudinal Data (Oxford Statistical Science Series Book 25)

COPY LINK: https://pdf.bookcenterapp.com/yumpu/B00DRD488M The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models fordiscrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This secondedition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes two new chapters the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.

COPY LINK: https://pdf.bookcenterapp.com/yumpu/B00DRD488M

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models fordiscrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This secondedition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes two new chapters the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.

SHOW MORE
SHOW LESS
  • No tags were found...

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Analysis of Longitudinal Data (Oxford

Statistical Science Series Book 25)

.


Analysis of Longitudinal Data (Oxford

Statistical Science Series Book 25)

Simple Step to Read and Download:

1. Create a FREE Account

2. Choose from our vast selection of EBOOK and PDF

3. Please, see if you are eligible to Read or Download book Analysis of Longitudinal Data (Oxford Statistical Science

Series Book 25)

4. Read Online by creating an account Analysis of Longitudinal Data (Oxford Statistical Science Series Book 25) READ

[MAGAZINE]


Analysis of Longitudinal Data (Oxford

Statistical Science Series Book 25)

DESCRIPTION

COPY LINK: https://pdf.bookcenterapp.com/yumpu/B00DRD488M The first edition of Analysis for

Longitudinal Data has become a classic. Describing the statistical models and methods for the

analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its

application to a range of examples from the agricultural and biomedical sciences. The main topics

discussed are design issues, exploratory methods of analysis, linear models for continuous data,

general linear models fordiscrete data, and models and methods for handling data and missing

values. Under each heading, worked examples are presented in parallel with the methodological

development, and sufficient detail is given to enable the reader to reproduce the author's results

using the data-sets as an appendix. This secondedition, published for the first time in paperback,

provides a thorough and expanded revision of this important text. It includes two new chapters the

first discusses fully parametric models for discrete repeated measures data, and the second

explores statistical models for time-dependent predictors.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!