Resources

This page lists commonly-used large-N datasets and resources for Data Analysis and Management.

Data Analysis and Management

• UMN Data Management Bootcamp

• UMN Software Carpentry Workshop (Workshop Materials, Introduction to LaTeX Typesetting)

• UMN LATIS Research Workshop (Workshop Materials)

• Minnesota Supercomputing Institute Workshop

• The Many Faces of Reproducibility (UMN)

• Data Cleaning for Data Sharing using R (Lewis)

• R Bootcamp and Social Network Analysis Bootcamp (Reuning)

• Training Computational Social Science PhD Students (Kim)

General Resources

• Harvard Dataverse Social Sciences Data

• ICPSR Dataverse

American Politics

• American National Election Study (ANES)

• General Social Survey (GSS)

• National Annenberg Election Survey (NAES)

• Assoc. of Religion Dataset Archives (ARDA)

• Pew Datasets (e.g. US Politics, Religion, Social Trends)

• World Values Survey (WVS)

IR and Comparative

• Correlates of War (COW)

• Issue Correlates of War (ICOW)

• Alliance Treaty Obligations and Provisions (ATOP)

• Global Terrorism Database (START)

• Mapping Militant Organizations (Stanford)

• Varieties of Democracy (V-Dem)

• Polity V (Center for Systemic Peace)

• Armed Conflict (PRIO)

• Mapping Arms Data Project (PRIO)

• Uppsala Conflict Data Program

Causal Inference

Publicly Accessible Books and Articles

• Causal Inference: What If (Hernan et al)

• Causal Inference: The Mixtape (Cunningham)

• The Effect: An Introduction to Research Design and Causality (Huntington-Klein)

• Causal Inference for the Brave and True (Facure)

• Partially Accessible: Mastering 'Metrics (Angrist and Pischke), The Book of Why (Pearl), Mostly Harmless Econometrics (Angrist and Pischke), Explanation in Causal Inference (Vanderweele), How to Make Causal Inferences Using Texts (Egami et al.)

Publicly Accessible Workshop Materials

• Mixtape Sessions

• Introduction to Causal Inference Course: From a Machine Learning Perspective (Neal)

• Northwestern Causal Inference Workshop Readings

• Yale Applied Empirical Methods Course (Goldsmith-Pinkham)

• Stanford Online Causal Inference Seminar

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