Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
(net)
price for USA
ISBN 978-1-4419-5557-9
digitally watermarked, no DRM
Included Format: PDF and EPUB
download immediately after purchase
Softcover (also known as softback) version.
You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.
Standard shipping is free of charge for individual customers.
(net)
price for USA
ISBN 978-1-4419-5556-2
free shipping for individuals worldwide
usually dispatched within 3 to 5 business days
Linear models courses are often presented as either theoretical or applied. Consequently, students may find themselves either proving theorems or using high-level procedures like PROC GLM to analyze data. There exists a gap between the derivation of formulas and analyses that hide these formulas behind attractive user interfaces. This book bridges that gap, demonstrating theory put into practice.
Concepts presented in a theoretical linear models course are often trivialized in applied linear models courses by the facility of high-level SAS procedures like PROC MIXED and PROC REG that require the user to provide a few options and statements and in return produce vast amounts of output. This book uses PROC IML to show how analytic linear models formulas can be typed directly into PROC IML, as they were presented in the linear models course, and solved using data. This helps students see the link between theory and application. This also assists researchers in developing new methodologies in the area of linear models.
The book contains complete examples of SAS code for many of the computations relevant to a linear models course. However, the SAS code in these examples automates the analytic formulas. The code for high-level procedures like PROC MIXED is also included for side-by-side comparison. The book computes basic descriptive statistics, matrix algebra, matrix decomposition, likelihood maximization, non-linear optimization, etc. in a format conducive to a linear models or a special topics course.
Also included in the book is an example of a basic analysis of a linear mixed model using restricted maximum likelihood estimation (REML). The example demonstrates tests for fixed effects, estimates of linear functions, and contrasts. The example starts by showing the steps for analyzing the data using PROC IML and then provides the analysis using PROC MIXED. This allows students to follow the process that lead to the output.
Content Level » Research
Keywords » Descriptive statistics - IML - Interactive matrix language - Linear mixed models - Mathematica - Matrix book - Nonlinear optimization - SAS - SAS matrices - SAS/IML - STATISTICA - Statistical modeling
Related subjects » Computational Science & Engineering - Probability Theory and Stochastic Processes - Statistical Theory and Methods
Get alerted on new Springer publications in the subject area of Probability Theory and Stochastic Processes.