This program encompasses a wide variety of projects that actively develop innovative methods and software as a way of building and unifying the methodological subfields now existing separately within most social science disciplines.  In this way, participants help to restructure the fundamental concept and applications of quantitative methodology within the arena of social science.

Projects and initiatives with which the PQM is involved include:

• Applied Statistics Workshop (GOV 3009) - This weekly workshop is offered Wednesdays at noon in CGIS, with many faculty, students, and other scholars attending regularly to discuss statistical innovations and applications.  Participating is a great way to learn about the community at IQSS that is focused on statistical methods. See http://www.iq.harvard.edu/applied_statistics_workshop_gov_3009.
• Social Science Statistics blog - The program hosts a blog to enable free exchange of relevant information among program and discipline participants. It serves to formalize and record some of the numerous hallway conversations going on about social science statistics.  See http://iq.harvard.edu/blog/sss.
• The Dataverse Network application - IQSS hosts a publicly available installation of the Dataverse Network software, an open source data sharing and archiving web application developed and maintained by the Dataverse Network Project at the IQSS. Each Dataverse Network installation consists of individual dataverses, or virtual archives, for storing, preserving, distributing, and sharing data. Uploading data to this repository helps ensure that scholars receive formal citation credit, increased attention for writings, and increased web visibility. See http://www.iq.harvard.edu/projects/dataverse_network.
• RCE - The Research Computing Environment (RCE) supplies a persistent desktop environment that is accessible from any computer with an internet connection. It offers a centralized place in which to store data, run analysis, and collaborate with other researchers.  Access is provided to numerous statistical analysis packages, including R, GAUSS, Mathematica, MATLAB, Octave, SAS, S-Plus, Stata, and SPSS. To support use of those tools for large-scale analysis, the RCE includes multiple cluster computing resources. See http://support.hmdc.harvard.edu/kb-1066/accessing_rce_overview.
• rbuild - The program rbuild.pl enables collaboration on development of R packages within the hosted RCE. The rbuild program can be run by any member of a collaborative team to maintain package updates automatically for all team members' use, providing email notification tools, compiling and publishing updated documentation, installing the latest package, and sending that package to the CRAN repository. See http://support.hmdc.harvard.edu/kb-373/automating_r_package_builds_summer_2009.

The Program also assists many researchers at the IQSS put together open source statistical software.  Examples include Zelig (http://gking.harvard.edu/zelig), the statsitical software in the Dataverse Network data repository (http://TheData.org), and many others.