Hello,
We hope you will join us this Wednesday, February 24th at the Applied
Statistics workshop when we will be happy to have Matt Killingsworth
(Department of Psychology). Details and an abstract are below. A light
lunch will be served. Thanks!
"Mind Wandering and Happiness
Matt Killingsworth
Department of Psychology
February 24th, 2010, 12 noon
K354 CGIS Knafel (1737 Cambridge St)
ABSTRACT:
Although humans spend much of their time mind-wandering, i.e.,
thinking about something other than what one is actually doing, little
is known about mind wandering's relation to human happiness. Using
novel technology to achieve the world's largest experience sampling
study of people's everyday lives, we found that participants spent
nearly half of their waking hours mind-wandering and that it had large
effects on happiness. Mind wandering was never observed to increase
happiness and often reduced happiness considerably. Although some
activities and situations modestly decreased the probability of mind
wandering, they generally did not buffer against negative thoughts
when a person's mind did stray from the present.
Hello all,
We hope you will join us this Wednesday, February 17th at the Applied
Statistics workshop when we will be happy to have Cassandra Wolos
Pattanayak (Department of Statistics). Details and an abstract are
below. A light lunch will be served. Thanks!
"Diagnostics for Covariate Balance: Propensity Score Analyses at the
Centers for Disease Control and Prevention" (Joint work with Donald B.
Rubin and the CDC)
Cassandra Wolos Pattanayak
Department of Statistics
February 17th, 2010, 12 noon
K354 CGIS Knafel (1737 Cambridge St)
ABSTRACT:
With propensity score analyses increasingly widespread, the crucial
step of scrutinizing the balance of covariates in the selected
treatment and control groups deserves emphasis. This talk focuses on
two recent collaborations with the CDC that highlight the importance
of diagnosing covariate balance at the design stage, without access to
study outcomes.
In the first application, we create matched treatment and control
groups to examine the effect of transferring one v. two embryos during
in vitro fertilization on pregnancy rates, multiple births, and other
outcomes. The matching process demonstrates the importance of
attention to detail in covariate selection and the use of balance
checking to choose a matching protocol. The second application
involves propensity score subclassification in a clinical trial
evaluating a possible prevention for perinatal sepsis in South Africa.
The clinical trial actually randomized patients to treatment or
placebo, and our analysis illustrates the possibilities for improving
covariate balance when faced with an "unlucky" randomization. Both
projects have been conducted without access to study outcomes and with
a focus on diagnostics.
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,
We hope you will join us this Wednesday, February 10th at the Applied
Statistics workshop when we will be happy to have Tyler VanderWeele
(Harvard School of Public Health). Details and an abstract are below.
A light lunch will be served. Thanks!
"Mediation and spillover effects in group-randomized trials: a case
study of the 4R's educational intervention."
Tyler VanderWeele
Department of Epidemiology and Biostatistics
Harvard School of Public Health
February 10th, 2010, 12 noon
K354 CGIS Knafel (1737 Cambridge St)
ABSTRACT:
In many group-randomized trials, questions of mediation are of
interest. In the education setting, often the treatment is at the
school level, the mediator is at the classroom level and the outcome
is at the individual level. The standard approach to mediation
analysis in the social sciences is subject to three important
shortcoming: (1) failure to account for possible treatment-mediator
interaction, (2) failure to account for mediator-outcome confounding
(even if the treatment is randomized the mediator is not and is thus
subject to selection-confounding issues) and (3) failure to account
for the spillover effects of one classroom on the outcomes of children
in other classroom. Ignoring any of these three issues can lead to
biases and misleading inferences. Using a counterfactual
conceptualization of direct, indirect and spillover effects, we
provide a framework that can accommodate all three of these issues.
We show that the total effect can be decomposed into what is defined
as a natural direct effect, a within-classroom mediated effect and a
spillover mediated effect. We give identification conditions for each
of the causal effects of interest and we provide theoretical results
on the sequences of ignoring "interference" or spillover effects when
they are in fact present. The methodology is applied to a
group-randomized trial of the 4R's educational intervention.
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,
I have posted a copy Matthew Baum's paper on the course website. Here
is the link:
http://isites.harvard.edu/fs/docs/icb.topic646669.files/Tabloid.pdf
We hope you can join us for Matt's talk at 12 noon tomorrow (Feb 3rd)
in K354 CGIS Knafel (1737 Cambridge St).
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,
We are happy to announce that we will have Matthew Baum of the Harvard
Kennedy School at the Applied Statistics workshop this Wednesday,
February 3rd at 12 noon. The title of the talk is "Political Scandal,
Gender, and Tabloid News: An Experimental Examination of the
Evolutionary Origins of Consumer Preferences for Scandalous News."
Matt has passed along the following abstract for the talk.
Abstract:
Building on recent work in evolutionary psychology, we predict
substantial gender- and self-image-related differences in demand for
scandalous political news. We argue that individuals’ relative
attractiveness can alter their motivation to seek information about
potential sexual competitors and mates, even when those figures are
“virtual”—appearing in mass media. We test our hypotheses using
national survey data, as well as experiments on student and
nationally-representative population samples. We find strong
correlations between respondents’ self-image and their likelihood of
seeking and distributing positive or negative information about
“virtual” competitors and mates.
The Applied Statistics workshop meets in room K354 of CGIS Knafel
(1737 Cambridge St) at 12 noon on Wednesdays. A light lunch will be
provided. 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/
