reference material

This page has additional information about:

• Administrative Data Research Facility (ADRF)

• Cheatsheets & tutorials

• Readings

Administrative Data Research Facility (ADRF)

The training program will be taught on the Administrative Data Research Facility (ADRF) - a secure computing environment developed by NYU. The goal of the ADRF is to encourage collaboration while preserving data confidentiality - it is designed following the Five Safes framework. For Administrative Data Research Facility (ADRF) documentation, please see the ADRF ReadTheDocs.

cheatsheets & tutorials

The below cheatsheets and tutorials were compiled during the 2017 training programs.

R Cheatsheets

• Data Wrangling with dplyr and tidyr

• Base R Cheatsheet

• R ggplot2 Cheatsheet

• R 2019 Compiled Cheatsheets

• Visualization Examples in R

Other Resources

• Linux/Unix common terminal commands

• Git 1-pager and web tutorial

• Regex

• Python 1-pager from DataCamp and longer version of general Python notes

• Pandas:

  • Drive folder with Python, Pandas, and Matplotlib notes,

  • short cheatsheet by Pandas dev team,

  • Pandas Cheatsheet

• Python's requests & BeautifulSoup libraries (for webscraping & APIs): link

• SQL Cheatsheet

• PostGIS: extensive function cheatsheet, and full function reference

  • Boundless Intro to PostGIS (great intro exercises)

  • Example of custom nearest neighbor function

• Spatial analysis in Python:

  • "Geographic Data Science with PySAL and the pydata stack" (Julia Koschinsky's colleagues Sergio Rey and Dani Arribas-Bel)

• Project scoping tutorial and worksheet from DSSG

• SciKit-Learn’s algorithm selection cheatsheet

readings

• Compiled papers on recidivism

• The social sciences need to build new foundations

• Worker Advancement in the Low-Wage Labor Market: The Importance of “Good Jobs” by Fredrik Andersson, Harry J. Holzer and Julia I. Lane

• Schnepel, Kevin T. "Good jobs and recidivism." The Economic Journal (2016)

• From College To Jobs: Making Sense Of Labor Market Returns To Higher Education

• Active labor market policy evaluations: a meta-analysis

• Transforming U.S. Workforce Development Policies for the 21st Century

• Does Federally-Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts using Longitudinal Data on Workers and Firms

• Temporary Help Agencies and the Advancement Prospects of Low Earners

• Record linkage readings

  • Record linkage by Herzog (guest speaker on Feb 22), Scheuren and Winkler

  • An Introduction to Probabilistic Record Linkage

  • Probabilistic Record Linkage after Indexing, Blocking, and Filtering

  • Record Linkage: Similarity Measures and Algorithms

  • Linking Data for Health Services Research: A Framework and Instructional Guide

  • Probabilistic Record Linkage: A Short Tutorial

• Disclosure limitation & Confidentiality

  • International Household Survey Network

  • Government Statistical Service

  • Whitehouse Statistical Policy Working Paper

  • Managing Statistical Confidentiality & Microdata Access

  • The modernization of statistical disclosure limitation at the U.S. Census Bureau

  • Differential Privacy: A Primer for a Non-technical Audience

  • An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices

  • Implications of Differential Privacy for Census Bureau Data and Research

  • How Modern Disclosure Avoidance Methods Could Change the Way Statistical Agencies Operate

• Text Analysis

  • Probabilistic Topic Models by Blei

  • Topic Modeling Workshop by Blei

  • Text as Data by Gentzkow, Kelly, and Taddy

• Spatial analytics readings recommended by Julia Koschinsky

  • Making a Place for Space: Spatial Thinking in Social Science by John R. Logan

  • PostGIS in Action (2nd edition)

  • The Analysis of Spatial Association by Use of Distance Statistics (Getis-Ord G statistics)

• Varied statistics, econometrics, and programming readings recommended by Tim Savage

  • Introduction to Python for Econometrics, Statistics and Data Analysis by Kevin Sheppard (free)

  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction

  • An Introduction to Statistical Learning with Applications in R

  • Causal Inference in Statistics: A Primer

  • Introduction to Data Linkage by Katie Harron

• Comparability Of Mortality Estimates by Brown