Longitudinal and Survival Analysis of Business Data:
A Two-Day Training Using the Kauffman Firm Survey
May 31- June 1, 2011
San Francisco, California, USA
August 11-12
San Antonio, Texas, USA
October 22-23 (tentative)
Washington, D.C., USA
Are you doing research using longitudinal business data but have questions
about what techniques are best suited to your hypotheses and the limitations
of data? Utilizing the Kauffman Firm Survey, a panel data set with six years
of data on businesses that began operations in the United States in 2004,
this short-course will provide a small-scale setting to explore research
techniques in longitudinal analysis of business data.
Longitudinal data offer many opportunities and potential pitfalls. With such
data, researchers can examine predictor and response variables at two or
more points in time. These kinds of data have two major attractions: the
ability to control for unobservables and the determination of causal
ordering. However, problems can arise if longitudinal data are not used
properly. Repeated observations typically are correlated and this
invalidates the usual assumption that observations are independent. In this
training we examine methods to deal with this dependence: robust standard
errors, generalized estimating equations, random effects models, and fixed
effects models. We also will examine different methods for quantitative
outcomes, categorical outcomes, count data outcomes, and survival analysis.
Who should attend?
This workshop is for researchers seeking to learn better methods for
analyzing longitudinal business data and have a basic statistical
background. The primary audience are researchers currently using the KFS for
analysis or who have an interest in possible research using the KFS.
Participants should have a good working knowledge of the principles and
practice of econometrics and statistics.
Cost
Participants will be expected to cover their own travel and lodging costs
but no registration fee will be charged for researchers who already have a
working paper using the KFS or who can provide an abstract of their planned
research using the KFS.
Technical Requirements
This workshop will use STATA (release 11) for the empirical examples.
Participants should bring their own laptops with either STATA or SAS.
Exercises will be assigned to complete during the evening between the two
days of coursework.
Course Outline
Day One:
1. Opportunities and challenges of panel data
* Data requirements
* Controlling for unobservables
* Determining causal order
* Problem of dependence
2. Linear models
* Robust standard errors
* Generalized estimating equations
* Random effects models
* Fixed effects models
* Hybrid models
3. Logistic regression models
* Robust standard errors
* Generalized estimating equations
* Subject-specific vs. population averaged methods
* Random effects models
* Fixed effects models
* Hybrid models
4. Count data models
* Poisson models
* Negative binomial models
* Fixed and random effects
5. Linear structural equation models
* Reciprocal causation with lagged effects
Day Two:
1. Fundamentals of survival analysis
* Problems with conventional methods
* Types of censoring
* Kaplan-Meier estimation
* Proportional hazards models
* Partial likelihood estimation
* Interpretation of parameters
* Competing risks
* Time dependent covariates
* Discrete time analysis
* Heterogeneity and time dependence
* R-squared
1. KFS Data: Specifics
* Missing data and imputation
* Summary of KFS research
Materials
Participants will receive a course packet containing detailed lecture notes,
examples of STATA output and KFS exercises, and information about the KFS
dataset, including research bibliography. The following sources provide the
foundation for the course: Fixed Effects Regression Methods for Longitudinal
Data Using Stata by Paul Allison; An Introduction to Survival Analysis Using
Stata by Cleves, Gould, and Gutierrez; and Marchenko, Course Packs on
Longitudinal Analysis and Survival Analysis using Stata by Paul Allison.
Instructor
Alicia Robb is senior research fellow at the Ewing Marion Kauffman
Foundation and is the principal investigator on the Kauffman Firm Survey.
Previously, she was an economist at the Division of Research and Statistics,
Board of Governors of the Federal Reserve System and an economist at the
Office of Economic Research at the U.S. Small Business Administration. A
leading expert on small business data in the U.S., she has a Ph.D. in
Economics from the University of North Carolina, Chapel Hill with a
specialization in econometrics.
Registration
Participation in each course will be limited to 12 researchers. Interested
participants should email
kfs@kauffman.org<mailto:
kfs@kauffman.org> <mailto:
kfs@kauffman.org>
and include their name, affiliation, contact information, preferred training
date, as well as a working paper using the KFS or an abstract of planned
research using the KFS. If you have specific skills or questions you would
like explored in the training, please also indicate that in your email.
Registration will be on a first come first served basis.
More information at
http://www.kauffman.org/kfs/Training-Opportunities/KFS101.aspx
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