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About this Cambridge Elements series

The foundation of this series will be short introductions and hands-on tutorials to innovative methodologies, those so novel they don’t have textbooks or other longer treatments as to their application.

Elements within the series on Cambridge Core are fast tracked after formal acceptance, they are updatable, and are available via low-priced POD. They will appeal to researchers and graduate students wanting to stay abreast of current methodology or learn new tools, and to instructors who wish to supplement course texts.

To view the latest published Elements in this Series, visit the Quantitative and Computational Methods for the Social Sciences series page


Contact the Editors

If you would like more information about this series, or are interested in writing an Element, email qcmsselements@cambridge.org

Areas of interest

Among emerging new areas of interest for social scientists, we are interested in presenting machine learning tools for social scientists, including text analysis, dataset linkage and merging, model specification, and data imputation. 

We are also interested in causal inference contributions on new approaches for estimating causal relationships.

Other areas of focus include sampling, multimode interviewing, sample weighting, the use of new technologies for the collection of collecting survey and polling data, and new techniques for conducting and analysing data from field, online, and laboratory experiments.