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New Books at the Methodology Center |
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Models for Intensive Longitudinal Data (2006)
Theodore A. Walls University of Rhode Island
Joseph L. Schafer Pennsylvania State University
New York, NY: Oxford University Press |  | A new class of longitudinal data has emerged as a result of the use of technological devices for data collection in diverse areas of scientific inquiry. For example, social scientific studies frequently utilize handheld computers, beepers, web interfaces and other technological tools for data collection. This class of data is called intensive longitudinal data (ILD) . The volume features state-of-the-art statistical modeling strategies developed by leading statisticians working in conjunction with scientists. | | Statistical modeling frameworks are outlined and each chapter includes an applied example or application with example programs to be archived on this site. |
Design and Modeling for Computer Experiments (2005)
Kai-Tai Fang Hong Kong Baptist University
Runze Li Pennsylvania State University
Agus Sudjianto Bank of America
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Volume: 6 | | | - Blends a modern, sound statistical approach with extensive practical engineering applications
- Presents numerous examples that clarify the methods and their implementation
- Presents the most useful design and modeling methods, including some original contributions from the authors
- Covers uniform design, measures of uniformity, and their algebraic approaches
- Discusses special techniques for model interpretation such as ANOVA and the Fourier Amplitude Sensitivity Test
|  | Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires careful interrogation of the model through systematic computer experiments. While specific theoretical/mathematical examinations of computer experiment design are available, those interested in applying proposed methodologies need a practical presentation and straightforward guidance on analyzing and interpreting experiment results.
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Developing Statistical Software in Fortran 95 (2005)
David R. Lemmon Pennsylvania State University
Joseph L.Schafer Pennsylvania State University
New York, NY: Springer |  | The purpose of this project is to develop strategies for:programming efficient and accurate statistical routines in Fortran, and arranging them in modules that are easy to reuse, maintain and extend; calling these routines from many applications, including Excel, SAS, SPSS, S-PLUS, R and MATLAB; and connecting them to graphical user interfaces (GUIs) written in languages such as Visual Basic and C#. | | | | |
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New Books