5-day MEAFA Professional Development Workshop on Quantitative Analysis Using Stata, 13 - 17 July 2009
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Examples of data analysis using Stata 10
Description
The professional development workshop is primarily aimed to social sciences researchers who wish to develop quantitative analysis skills using Stata 10 
. The 2009 workshop spans over five days and offers a variety of topics.
- Day 1 (July 13): Introduction to Stata 10 and the Management of Data
This day assumes no previous knowledge of Stata. It begins with introducing the environment of Stata 10 and unlocks some of the software's most subbtle aspects, followed by a demonstration of various data structures and an eclectic selection of data management techniques. - Day 2 (July 14): Econometric Modelling and Statistical Testing
This day assumes elementary knowledge of Stata 10 and a basic appreciation of quantitative analysis methods. This day will use applications to demonstrate the theory of basic econometric modelling including time-series forecasting and the use of statistical testing for validating assumptions and expectations. - Day 3 (July 15): Stata Proramming and Mata Secrets
This day assumes good knowledge of Stata 10. It demonstrates key programming Stata skills for building a more structured and methodical approach to quantitative analysis, and also shows how to use Mata (Stata's background matrix language) in order to enhance programming efficiency. - Day 4 (July 16): Survey Data Analysis
This day assumes good knowledge of Stata 10 and basic understanding of quantitative analysis. It introduces the concept of survey data analysis and explains its distinction to the other types of quantitative analysis. It uses the European Social Survey to apply the principles and concepts of empirical survey data analysis. - Day 5 (July 17): Panel Data analysis
This day assumes good knowledge of Stata 10 and good understanding of econometric modelling. It explains the rationale of panel data methods of analysis and then demonstrates static and dynamic models of panel data. It also covers the special class of mixed panel data structures that combine the dimensions of random and fixed effects.
This is a hands-on workshop, and all days have a strictly applied focus using real data or simulated datasets. Nonetheless, detailed notes will be provided outlining the theoretical foundations of all types of analysis demonstrated. You may attend any one day or any combination of days, and fees vary on the number of days attended (depending on availablity).
If you have no or little experience with Stata then you should attend Day 1 before progressing to the rest of the days. Similarly, if you do not feel comfortable with statistical or econometric modelling, then you should first attend Day 2. For more information on content see the detailed programme or contact meafa@econ.usyd.edu.au.
Stata 10
Stata 10 is a complete, integrated statistical package for data management, statistical analysis, graphing and econometric estimation. Stata is fast, accurate and easy to use. For more information visit StataCorp's website.
Computing Facilities and Venue
The workshop will take place at the Faculty of Economics and Business computer labs, Building H69 ground floor, cnr Codrington & Rose streets, the University of Sydney (see interactive map). You do not need to bring your own laptop. PCs and Stata 10 licenses for Microsoft Windows will be provided.
Enrolment
Numbers are limited and places are reserved on a first-come first-served basis. Successful attendees will be notified shortly after reservation and invoices will be issued accordingly. MEAFA maintains a no refund policy following payment. For more information on enrollment and fees contact meafa@econ.usyd.edu.au.
Fees
You may attend one or more days and fees vary on the number of days attended (prices exclude GST):
- Any one day: $550
- Any two days: $1000
- Any three days: $1450
- Any four days: $1900
- All five days: $2350
Fees include extensive course material, data sets, lectures, use of computing facilities, temporary Stata 10 licenses, full catering and opportunity to network with fellow researchers.
Discounts
You may qualify for one of the below discounts that are available:
- 50% discount for a restricted number of non-employed full-time PhD students
- 15% discount for additional attendees from the same private/public organisation
- 25% discount for additional attendees from the same academic institution
Presenters
- Day 1: Dr Demetris Christodoulou, MEAFA General Convenor.
- Day 2: Dr Andrey Vansev, MEAFA.
- Day 3: Mr Karl Keesman, Survey Design & Analysis Services Pty Ltd, Australia & NZ Stata representative.
- Day 4: Dr Richard Gerlach, MEAFA Quantitative Analysis Convenor.
- Day 5: Dr Vasilis Sarafidis, MEAFA.
Programme
Day 1: Monday 13 July 2009, Introduction to Stata 10 and the Management of Data |
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08:40 |
Welcome tea and coffee |
09:00-10:30 |
Introduction to Stata 10 Environment Stata environemnt; configuration and special features; updates; personalised system; directory management; obtain help and perform search; online sources; Stata syntax |
10:30-10:45 |
Morning break |
10:45-12:15 |
Data Formats and Data Handling Types of data formats; import, export, load and save datasets; create pseudorandom datasets; review and document the dataset; ordering of dataset; display format |
12:15-13:15 |
Lunch |
13:15-14:45 |
Data Structures and Types of Variables Categorical data; continuous data; append and merge other datasets; reorganise datasets; numerical, string and date/time variables; manage missing data; generate variables; dummy variables; generate other special purpose variables |
14:45-15:00 |
Afternoon break |
15:00-16:30 |
Data Management and Output Management Usable dataset and benefits of filtering; validate claims on data structure; identify duplicate observations; logs for output; copy & paste from Stata to text editors and spreadsheets; stored results |
16:30-17:00 |
Questions and User-Specific Issues |
Day 2: Tuesday 14 July 2009, Econometric Modelling and Statistical Testing |
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|---|---|
08:40 |
Welcome tea and coffee |
09:00-10:30 |
Statistical Description and Linear Regression Analysis Means, variances and higher order moments; medians and modes; confidence intervals; simple / multiple regressions with continuous and dummy variables; estimation; hypothesis testing; internal and external validity |
10:30-10:45 |
Morning break |
10:45-12:15 |
Statistical Description and Nonlinear Regression Functions General strategy for modelling nonlinear regression functions; polynomials / logarithms in regression; interactions between independent variables (including continuous and dummy variables); internal and external validity |
12:15-13:15 |
Lunch |
13:15-14:45 |
Introduction to Time Series Regressions and Forecasting Introduction to time series data; serial correlation; random walks; autoregressions; moving averages; regressions with additional predictors; autoregressive distributed lag model |
14:45-15:00 |
Afternoon break |
15:00-16:30 |
Testing for Time Series Validity Stochastic vs. deterministic trend; stationarity; testing for a unit root; testing for breaks; testing for trends; information criteria and lag length selection; ARMA models; forecasting |
16:30-17:00 |
Questions and User-Specific Issues |
Day 3: Wednesday 15 July 2009, Stata Programming and Mata Secrets |
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|---|---|
08:40 |
Welcome tea and coffee |
09:00-10:30 |
Introduction to do-files Storing and executing commands in do-files; writing long commands in do-files; difference between do and run; calling other do-files from a do-file; comments in do-files; passing arguments to the do-file; edit saved reviews from the results window |
10:30-10:45 |
Morning break |
10:45-12:15 |
Creating Programs Creating a program from a do-file; when to use a program; including a program in a do-file; the command clear and its use in programming; creating an ado file from a program |
12:15-13:15 |
Lunch |
13:15-14:45 |
Elements in a Program local macros; global macros; scalars; if statements; loops; the combination of preserve and restore; parsing elements; introduction to the syntax command |
14:45-15:00 |
Afternoon break |
15:00-16:30 |
Mata Secrets When to use Mata and when not to; getting data in Mata; looping; if statements; subscripting matrices; string and numerical matrices; getting a mata matrix into Stata; Mata functions; Mata optimize; Mata matrix maths; solving simultaneous equations using Mata |
16:30-17:00 |
Questions and User-Specific Issues |
Day 4: Thursday 16 July 2009, Survey Data Analysis |
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|---|---|
08:40 |
Welcome tea and coffee |
09:00-10:30 |
Introduction to Sampling and Survey Design Variable types; exploratory data analysis; rating scales: choices and pros/cons; question wording; simple random sampling; sampling with and without replacement; sampling distributions for means and proportions; European Social Survey |
10:30-10:45 |
Morning break |
10:45-12:15 |
Sampling Weights and Estimation Complex sampling methods; stratification; sampling weights; unequal selection probabilities; sample size determination; optimal sample size given design; adapting statistical analysis |
12:15-13:15 |
Lunch |
13:15-14:45 |
Advanced Sampling and Estimation Multi-stage sampling; cluster sampling; mixed sampling approaches; Horwitz-Thompson estimation; variance estimation; design effects; analysis of tables and testing; ratios; linear regression |
14:45-15:00 |
Afternoon break |
15:00-16:30 |
Advanced Survey Estimation Multiple linear regression; logistic regression; ordinal regression; dignostics; graphing; examples from European Social Survey |
16:30-17:00 |
Questions and User-Specific Issues |
Day 5: Friday 17 July 2009, Panel Data Analysis |
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08:40 |
Welcome tea and coffee |
09:00-10:30 |
Introduction to Panel Data Analysis Advantages of panel data analysis; panel data sets; balanced and unbalanced panels; panel data dimensions and frequencies; properties of estimators; unbiasedness; efficiency; consistency; describing panel data; graphing panel data |
10:30-10:45 |
Morning break |
10:45-12:15 |
Static Linear Models Specification and estimation; one-way and two-way error components; fixed and random effects; the Least Squares Dummy Variable model; the Within, Between and GLS estimators; the Hausman test; variance decomposition |
12:15-13:15 |
Lunch |
13:15-14:45 |
Dynamic Linear Models Nickell biases; Anderson-Hsiao IV estimation; the problem and tests of weak instruments; the Generalised Method of Moments; testing for overidentifying restrictions; cross sectional dependence |
14:45-15:00 |
Afternoon break |
15:00-16:30 |
Mixed Models of Panel Data Panel data modes with both fixed and random effects; syntax for the -xtmixed- command; random intercepts; random slopes; estimation of variances and covariances; multiple levels and nested effects; error distributions; postestimation |
16:30-17:00 |
Questions and User-Specific Issues |