This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
Latest Version Dependencies status unknown Test status unknown Test coverage unknown
Project Description

ipt: a Python 2.7 package for causal inference by inverse probability tilting

by Bryan S. Graham, UC - Berkeley, e-mail: bgraham@econ.berkeley.edu

This package includes a Python 2.7 implementation of the Average Treatment Effect of the Treated (ATT) estimator introduced in Graham, Pinto and Egel (2016). The function att() allows for sampling weights as well as “clustered standard errors”, but these features have not yet been extensively tested.

An implementation of the Average Treatment Effect (ATE) estimator introduced in Graham, Pinto and Egel (2012) is planned for a future update.

This package is offered “as is”, without warranty, implicit or otherwise. While I would appreciate bug reports, suggestions for improvements and so on, I am unable to provide any meaningful user-support. Please e-mail me at bgraham@econ.berkeley.edu

Please cite both the code and the underlying source articles listed below when using this code in your research.

A simple example script to get started is:

>>>> # Append location of ipt module root directory to systems path
>>>> # NOTE: Only required if ipt not "permanently" installed
>>>> import sys
>>>> sys.path.append('/Users/bgraham/Dropbox/Sites/software/ipt/')

>>>> # Load ipt package
>>>> import ipt as ipt

>>>> # View help file
>>>> help(ipt.att)

>>>> # Read nsw data directly from Rajeev Dehejia's webpage into a
>>>> # Pandas dataframe
>>>> import numpy as np
>>>> import pandas as pd

>>>> nsw=pd.read_stata("http://www.nber.org/~rdehejia/data/nsw_dw.dta")

>>>> # Make some adjustments to variable definitions in experimental dataframe
>>>> nsw['constant'] = 1                # Add constant to observational dataframe
>>>> nsw['age']      = nsw['age']/10    # Rescale age to be in decades
>>>> nsw['re74']     = nsw['re74']/1000 # Recale earnings to be in thousands
>>>> nsw['re75']     = nsw['re75']/1000 # Recale earnings to be in thousands

>>>> # Treatment indicator
>>>> D = nsw['treat']

>>>> # Balancing moments
>>>> t_W = nsw[['constant','black','hispanic','education','age','re74','re75']]

>>>> # Propensity score variables
>>>> r_W = nsw[['constant']]

>>>> # Outcome
>>>> Y = nsw['re78']

>>>> # Compute AST estimate of ATT
>>>> [gamma_as, vcov_gamma_ast, study_test, auxiliary_test, pi_eff_nsw, pi_s_nsw, pi_a_nsw, exitflag] = \
>>>>                                                                 ipt.att(D, Y, r_W, t_W, study_tilt=True)

CODE CITATION

Graham, Bryan S. (2016). “ipt: a Python 2.7 package for causal inference by inverse probability tilting,” (Version 0.2.2)
[Computer program]. Available at https://github.com/bryangraham/ipt (Accessed 04 May 2016)

PAPER CITATIONS

Graham, Bryan S., Cristine Pinto and Daniel Egel. (2012). “Inverse probability tilting for moment condition models
with missing data,” Review of Economic Studies 79 (3): 1053 - 1079
Graham, Bryan S., Cristine Pinto and Daniel Egel. (2016). “Efficient estimation of data combination models by the
method of auxiliary-to-study tilting (AST),” Journal of Business and Economic Statistics 31 (2): 288 - 301
Release History

Release History

0.2.3

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
ipt-0.2.3.tar.gz (13.8 kB) Copy SHA256 Checksum SHA256 Source Sep 16, 2016

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS HPE HPE Development Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting