Hello all,
We hope you can join us this Wednesday, December 2nd for the final
Applied Statistics Workshop of the term, when we will have Adam Glynn
(Department of Government) presenting his talk entitled "What Can We
Learn with Statistical Truth Serum?" Adam has provided the following
abstract:
Due to the inherent sensitivity of many survey questions, a number of
researchers have adopted indirect questioning techniques in order to
minimize bias due to dishonest or evasive responses. Recently, one
such technique, known as the list experiment (and also known as the
item count technique or the unmatched count technique), has become
increasingly popular due to its feasibility in online surveys. In this
talk, I will present results from two studies that utilize list
experiments and discuss the implications of these results for the
design and analysis of future studies. In particular, these studies
demonstrate that, when the key assumptions hold, standard practice
ignores relevant information available in the data, and when the key
assumptions do not hold, standard practice will not detect some
detectable violations of these assumptions.
A copy of the companion paper will appear on our website shortly:
http://isites.harvard.edu/icb/icb.do?keyword=k64817
The workshop will begin at 12 noon with a light lunch and wrap up by
1:30. We meet in room K354 of CGIS Knafel (1737 Cambridge St). We hope
you can make it.
Cheers,
matt.
Hello all,
This is just a friendly reminder than there will be no Applied
Statistics Workshop this week due to the Thanksgiving holiday. We hope
that you will join us next Wednesday, December 2nd, when we will have
Adam Glynn (Government) presenting a talk entitled "What Can We Learn
with Statistical Truth Serum?"
Happy Thanksgiving,
matt.
Hello all,
Please join us at the Applied Statistics workshop this Wednesday,
November 18th at 12 noon when we will be happy to have Jim Greiner of
the Harvard Law School presenting on "Exit Polling and Racial Bloc
Voting: Combining Individual-Level and R x C Ecological Data." Jim has
provided a companion paper with the following abstract:
Despite its shortcomings, cross-level or ecological inference remains
a necessary part of many areas of quantitative inference, including in
United States voting rights litigation. Ecological inference suffers
from a lack of identification that, most agree, is best addressed by
incorporating individual-level data into the model. In this paper, we
test the limits of such an incorporation by attempting it in the
context of drawing inferences about racial voting patterns using a
combination of an exit poll and precinct-level ecological data;
accurate information about racial voting patterns is needed to trigger
voting rights laws that can determine the composition of United States
legislative bodies. Specifically, we extend and study a hybrid model
that addresses two-way tables of arbitrary dimension. We apply the
hybrid model to an exit poll we administered in the City of Boston in
2008. Using the resulting data as well as simulation, we compare the
performance of a pure ecological estimator, pure survey estimators
using various sampling schemes, and our hybrid. We conclude that the
hybrid estimator offers substantial benefits by enabling substantive
inferences about voting patterns not practicably available without its
use.
==
You can find a copy of the paper here:
http://isites.harvard.edu/fs/docs/icb.topic646669.files/RxCEcolInfWithEP.pdf
You can find the technical appendix here:
http://isites.harvard.edu/fs/docs/icb.topic646669.files/TexAppForAnnalsAppS…
The workshop will be in CGIS Knafel (1737 Cambridge St) room K354 and
we will start at 12 noon with a light lunch. We hope to see you there.
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
Hello all,
Due to Veteran's Day, there will be no meeting of Applied Statistics
Workshop this Wednesday, November 11th. We hope you will join us next
week, November 18th, when we will have Jim Greiner of the Harvard Law
School presenting "Exit Polling and Racial Bloc Voting: Combining
Individual-Level and R x C Ecological Data." If you would like to read
up on Jim's talk in advance, there is a copy of the relevant paper on
the course site:
http://isites.harvard.edu/icb/icb.do?keyword=k64817
Thanks,
matt.
Hi all,
I hope you can join us at the Applied Statistics Workshop this
Wednesday, November 4th, when we will be happy to have Edo Airoldi,
Assistant Professor in the Department of Statistics here at Harvard.
Edo will be presenting a talk entitled "A statistical perspective on
complex networks" for which he has provided the following abstract:
Networks are ubiquitous in science and have become a focal point for
discussion in everyday life. Formal statistical models for the
analysis of network data have emerged as a major topic of interest in
diverse areas of science, as many scientific inquiries involve
collections of measurements on pairs of objects. Probability models on
graphs date back to 1959. Along with empirical studies in social
psychology and sociology from the 1960s, these early works generated
an active network community and a substantial literature in the 1970s.
This effort moved into the statistical literature in the late 1970s
and 1980s, and the past decade has seen a burgeoning network
literature in statistical physics and computer science. The growth of
the World Wide Web and the emergence of online networking communities
such as Facebook and LinkedIn, and a host of more specialized
professional network communities has intensified interest in the study
of networks and network data. In this talk, I will review a few ideas
that are central to this burgeoning literature. I will emphasize
formal model descriptions, and pay special attention to the
interpretation of parameters and their estimation. I will conclude by
describing open problems and challenges for machine learning and
statistics.
The workshop will be begin at 12 noon with a light lunch. We usually
wrap up around 1:30p. We hope you can make it.
Cheers,
matt.
~~~~~~~~~~~
Matthew Blackwell
PhD Candidate
Institute for Quantitative Social Science
Department of Government
Harvard University
email: mblackwell(a)iq.harvard.edu
url: http://people.fas.harvard.edu/~blackwel/
