This is a collection of books and articles that we have found useful for background reading in the areas of basic statistical principles, experimental design, analysis, and functional neuroimaging.
The items in the Statistics group are listed in their approximate order of complexity. If you are somewhat removed from statistics coursework, the books by Howell and Cohen are extremely readable and practical introductions to the basic statistical principles underlying data analysis in experimental applications.
The items in the Experimental Design and Analysis section provide more advanced treatments of the application of multiple regression and analysis of variance to experimental designs of the type commonly encountered in functional neuroimaging experiments.
The items in the SPM list cover the theoretical background and implementation details of SPM in its various incarnations.
The Imaging books provide some background to structural and functional imaging.
R is a statistical computing language that is growing rapidly in both scope and popularity. Like SPM, it is distributed with an open-source license and comes with extensive documentation. Having reached the limits of statistical modeling complexity possible with SPM, you may find R to be an attractive and complementary working environment.
Statistics (Fifth Edition)
Draper and Smith (1998)
Aiken and West (1991)
Rosenthal, Rosnow and Rubin (2000)
West, Welch and Galecki (2007)
van Belle (2008)
Ziliak and McCloskey (2008)
Bland et al. (2009)
Experimental Design and Analysis
Keppel and Wickens (2004)
Keppel and Zedeck (1989)
Designing Experiments and Analyzing Data (Second Edition)
Maxwell and Delaney (2004)
McNeil, Newman and Kelly (1996)
Winer, Brown and Michels (1991)
Myers and Well (2002)
Friston et al. (2006)
Huettel, Song and McCarthy (2009)
Field, Miles and Field (2012)
Data Analysis and Graphics Using R (Second Edition)
Maindonald and Braun (2007)