Tony Berber Sardinha is Professor of Applied Linguistics at the Pontifical Catholic University in São Paulo, Brazil.Marcia Veirano Pinto is Adjunct Professor of English at the Federal University in São Paulo, Brazil.

• PrefaceIntroduction, Tony Berber Sardinha and Marcia Veirano Pinto (São Paulo Catholic University, Brazil)Part I: Understanding the principles: origins of the method, corpus design and annotation1. Multi-dimensional analysis: a historical synopsis, Douglas Biber (Northern Arizona University, USA) 2. Corpus design and representativeness, Jesse Egbert (Brigham Young University, USA)3. Tagging and counting linguistic features for multi-dimensional analysis, Bethany Gray (Iowa State University, USA)4. The Multi-dimensional Analysis Tagger, Andrea Nini (Aston University, UK)Part II: Conducting an MD analysis: Quantitative and qualitative analysis5. Multivariate statistics commonly used in multi-dimensional analysis, Pascual Cantos Gomez (University of Murcia, Spain) 6. Doing multi-dimensional analysis in SPSS, SAS and R, Jesse Egbert (Northern Arizona University, USA) and Shelley Staples (Purdue University, USA)7. From factors to dimensions: interpreting linguistic co-ocurrence patterns, Eric Friginal (Georgia State University, USA) and Jack Hardy (Emory College of Arts and Science, USA)8. Adding registers to a previous multi-dimensional analysis, Tony Berber Sardinha, Marcia Veirano Pinto, Carlos Kauffmann, Carolina Zuppardi and Cristina Mayer Acunzo (São Paulo Catholic University, Brazil)Part III. Exploring the method 9. Examining lexical and cohesion differences in discipline specific writing using MDA, Scott A. Crossley, Kristopher Kyle and Ute Römer (Georgia State University, USA)10. Using Discriminate Function Analysis in multi-dimensional analysis, Marcia Veirano Pinto (São Paulo Catholic University, Brazil)11. Using multidimensional analysis to detect representations of national identity, Tony Berber Sardinha (São Paulo Catholic University, Brazil)BibliographyIndex

The contributors to this volume, leading figures in multi-dimensional analysis, bring in these chapters experience and expertise to enhance existing corpus linguistics resources. The reader will accordingly find both a richness of analysis as well as clarity in explanation of MDA procedures. Essential reading for all researchers using corpus methods who wish to understand how register patterns vary, how the variation may be pinned down, and how such variation relates to underlying situational, social, and cognitive functions.