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The 2018 Stata Winter School
 
Venue: Hotel Birger Jarl Conference
Stockholm, Sweden  

Date:  February 19-23, 2018

 

Every year Metrika organizes a Stata Winter School in Stockholm. These winter schools represent a unique opportunity for students, academics, and professionals to expand their skills in data management and data analysis and to learn how these skills can be applied to their own fields. All courses combine teaching and problem solving, and there are ample opportunities for participants to ask questions and to receive individualized guidance. 

The 2018 Winter School is jointly organized by Metrika Consulting and Statistical Horizons and this makes it possible to offer an excellent set of courses taught by experienced Stata users and effective teachers of statistical methods:

  • Introduction to Stata. Dr. Peter Hedström, Linköping University/Metrika Consulting (February 19)
  • Longitudinal Data Analysis. Dr. Paul Allison, University of Pennsylvania/Statistical Horizons (February 20-21)
  • Survival Analysis. Dr. Paul Allison, University of Pennsylvania/Statistical Horizons (February 22-23)

 

Pleasclick here to sign up for the Stata Winter School.

 

 

Introduction to Stata (February 19)

This is a one-day introductory course for everyone who is interested in learning how to use Stata. No prior knowledge of Stata is required. The course offers a basic introduction to Stata and to data management using Stata. Once you have completed this course you will know the basics of Stata and be able to use it in your own research. The course also is an excellent foundation for the other courses in the Winter School. 

 

Course outline

  • How the Stata interface is organized: review window, variables window, results windows, do-file editor, data browser, etc.
  • The basic Stata commands.
  • Setting up your data: file management, recoding, and transforming data.
  • How to save your results in log files.
  • Reading data into Stata from non-Stata files.
  • Recoding and transforming variables.
  • Variable and value labels.
  • Reshaping your data.
  • Merging two or more data files.
  • How to work with do-files.
  • How to tabulate and graph your data.
  • How to estimate linear regression models
  • How to calculate and graph the marginal effects of covariates in regression-like models.

 

Stata commands covered include use, save, import, export, list, browse, edit, describe, summarize, in, if, by, sort, generate, egen, replace, recode, regress, rename, drop, keep, reshape, merge, append, tabulate, graph, margins, marginsplot.

 

Instructor

Peter Hedström is Professor of Analytical Sociology at Linköping University, and a Fellow of the Royal Swedish Academy of Sciences. He is the founder of Metrika Consulting, and an experienced user and teacher of Stata.

 

 

Longitudinal Data Analysis (February 20-21)

In this two-day course, you will learn how to do regression analysis of panel data—the most common type of longitudinal data. Panel data contain measurements of predictor and response variables at two or more points in time for many individuals. Although panel data have many attractions, the downside is that repeated measurements typically violate assumptions of independence.
This seminar covers four methods for solving the problem of dependent observations: robust standard errors, generalized estimating equations, random effects (mixed) models and fixed effects models. You'll learn how to use these methods for quantitative outcomes, categorical outcomes, and count data outcomes.
 
Here are a few of the topics that will be covered:

  • How to use panel data to control for unobserved variables.
  • Why fixed effects methods often give very different results from random effects methods.
  • How to reshape data from long form to wide form and back again.
  • Why the default correlation structure for GEE is usually not the best.
  • The difference between maximum likelihood and restricted maximum likelihood.
  • How to estimate and interpret random coefficients models.
  • Why first-order autoregressive structures are usually unsatisfactory.
  • The difference between subject-specific and population-averaged coefficients, and why it matters.
  • How to do longitudinal analysis using ordered logit or multinomial logit.

 

We will cover the following Stata commands: reg, areg, xtreg, xtmixed, logit, ologit, clogit, mlogit, xtlogit, xtmelogit, xtgee, xtpoisson, xtnbreg, mixed, melogit, mepoisson, menbreg, meologit, meglm, sem, and reshape.

 

Course outline

1. Opportunities and challenges of panel data.
  a. Data requirements
  b. Control for unobservables
  c. Determining causal order
  d. Problem of dependence
  e. Software considerations

2. Linear models
  a. Robust standard errors
  b. Generalized estimating equations
  c. Random effects models
  d. Fixed effects models
  e. Hybrid models

3. Logistic regression models
  a. Robust standard errors
  b. Generalized estimating equations
  c. Subject-specific vs. population averaged methods
  d. Random effects models
  e. Fixed effects models
  f. Hybrid models

4. Count data models
  a. Poisson models
  b. Negative binomial models
  c. Fixed and random effects

5. Linear structural equation models
  a. Fixed and random effects in the SEM context
  b. Models for reciprocal causation with lagged effects

 

Instructor 

Paul Allison is Professor of Sociology at the University of Pennsylvania, and the President of Statistical Horizons. He is a Fellow of the American Statistical Association, and a two-time winner of the American Statistical Association’s award for “Excellence in Continuing Education.”

 

 

Survival Analysis (February 22-23)

This two-day course covers both the theory and practice of survival methodology. Assuming no previous knowledge of survival analysis, this seminar will cover the essential tools needed to do time-to-event analysis. Topics include censoring, Kaplan-Meier estimation, Cox regression, time-dependent covariates, competing risks, discrete-time analysis, heterogeneity, stratification, and repeated events.

Stata commands covered include stset, sts list, sts graph, sts test, stcox, stcurve, logistic, cloglog and stcrreg.

 

Course outline

  • 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
  • Sensitivity analysis for censoring
  • Choice of time axis
  • Testing the proportional hazards assumption
  • Stratification
  • Heterogeneity and time dependence
  • Repeated events
  • Left censoring, left truncation

 

Instructor

Paul Allison is Professor of Sociology at the University of Pennsylvania, and the President of Statistical Horizons. He is a Fellow of the American Statistical Association, and a two-time winner of the American Statistical Association’s award for “Excellence in Continuing Education.”

 

 

Logistics

The Winter School is held at Hotel Birger Jarl and they offer discounted accommodation for all course participants (please contact us for further details). 

Please register for the courses you want to attend by sending us an email.

Attendance is limited and places are allocated on a first come, first serve basis. Please register long in advance to guarantee your place.

Stata 15 software is provided free of charge to all participants during the courses but participants are assumed to bring their own laptops.

 

Prices

Introduction to Stata

  • Academic and student            435 USD
  • Non-academic                         600 USD

 

Longitudinal Data Analysis or Survival Analysis

  • Academic and student            870 USD
  • Non-academic                       1450 USD

 

Introduction and (Longitudinal Data Analysis or Survival Analysis)

  • Academic and student           1150 USD
  • Non-academic                       1730 USD

 

Longitudinal Data Analysis and Survival Analysis

  • Academic and student           1459 USD
  • Non-academic                        2020 USD

 

Introduction and Longitudinal Data Analysis and Survival Analysis

  • Academic and student            1900 USD
  • Non-academic                         2700 USD

 

Please click here to sign up.


Please observe

  • All courses start at 9:00 and end at 17:00.
  • These prices do not include Swedish VAT/moms and they will be charged in SEK as of the day's currency exchange rate according to Sveriges Riskbank.
  • Faculty members and students must provide a proof of their current university affiliation at the time of booking (valid university email address for academics, and valid student ID card or official letter of enrollment for students)
  • The price includes course materials, lunch and refreshments (you will need to notify us well in advance in case of special dietary requirements)
  • These courses will be given in English.

 

Terms & conditions

  • Only paid participants are guaranteed places in the courses.
  • 100% of the fee is returned for cancellations made over six weeks prior to start of the course.
  • 50% of the fee is returned for cancellations made three weeks prior to the start of the course.
  • No fee is returned for cancellations made less than three weeks prior to the start of the course.

 

 

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