2017 Stats Camp: Summer Statistical Institute

Graduate students, faculty, post doctoral fellows, staff, and others are invited to attend the KU Stats Camp. This year, we are offering three weeks of sessions about R, Stata, and Structural Equation Modeling. KU Stats Camp begins in the last week of May and continues through the first two weeks of June. Participants are encouraged to enroll for all sessions in each week. Please see an in-depth description of each Stats Camp Track below.

Registration is open to KU students, faculty, and staff, as well as corporate employees or affiliates of other universities.  The daily price of attendance for KU affiliates is $50, while the daily price for others is $70.

 

Housing Options for Out-of-Town Attendees

The CRMDA has cooperative relationships with local hotels. We refer guests to the Double Tree by Hilton (special rate: $99/night). You must enter the Group Code of CRMDA to receive the special rate for a king room. Alternatively, call the Double Tree at 785-841-7077 and tell them you are with the CRM group.

We also refer guests to the Halcyon House Bed & Breakfast. Guests can call 785-841-0314 to make a reservation, at which time you should inquire about the KU rates.

We have access to a limited number of positions in KU Guest Housing. Space will be filled on a first-come-first-serve basis. In 2017, the nightly rate is $40 for a one bedroom apartment. Some two bedroom apartments are available for $50 per night. Visitors who intend to stay in campus housing must check in between 3PM and 5PM. Reservations must be made through the CRMDA offices.  Please contact Jennifer Schmitendorf via email or phone: 785-864-3353 to request a reservation for campus accommodation.

If you have questions, please contact Jennifer Schmitendorf via crmda@ku.edu or phone: 785-864-3353.

Parking on Campus

Our sessions are offered on the main campus of the University of Kansas. Daily and Weekly parking passes are available from the KU Parking Department located at 1501 Irving Hill Road, Lawrence, KS 66045. To obtain a pass, it is necessary for visitors to go to the Parking office. The Parking office recommends visitors phone ahead (785-864-7275) so that some paperwork and payment can be completed in advance. Tell them you are with the CRMDA Summer Statistical Institute to receive the reduced price for a weekly pass of $21 (daily price is $6).

 

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There will be 30 seats open in each workshop.  Enrollment (as well as refund eligibility) will cease at the close of business (5pm CST) May 15th2017. If you need special consideration, please contact the CRMDA at crmda@ku.edu.

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CRMDA 2017 Summer Institute Course Descriptions

Sessions daily 9am-12pm & 1:30pm-4pm

 

Week 1: R.

Day 1 05/22

Getting to Know R

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • R User Interface, accessing documentation, code preparation, help pages.
  • Line Art: publication quality illustration and technical drawings.

Day 2 05/23

Establishing a Replicable Research Process

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Data Import, recoding.
  • Graphical exploration.
  • Exporting tables for reports.

Day 3 05/24

Statistical Analysis the R Way

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Regression & ANOVA,
  • Structural Equation Modeling
  • Moderation and Mediation

Day 4 05/25

R Toolkit for Interacting with Data

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Matrix Algebra with R
  • Iteration, data subsets.
  • Creating R functions to customize projects

Day 5 05/26

Monte Carlo Programming & Power Analysis

Instructor: Dr. Paul Johnson and Dr. Ben Kite

  • Monte Carlo simulation in R
  • Power analysis: definition and implications
  • Using Monte Carlo simulation to estimate power

 

Week 2 - Stata. Watson Library, Room 455

Day 6 05/30

An Introduction to Stata for Statistical Analysis

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Learn important concepts and best practices for quantitative analysis in the social sciences.
  • Demonstrate how these conventions can be implemented using Stata.
  • Review the Stata interface, beginning with point and click menus and progressing to basic programming.

Day 7 06/31

Reliable and Reproducible Workflows Using Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Lean to write and debug simple Stata programs using built-in do-file editor. 
  • Demonstrate best practices in writing do-files and simple options for identifying and correcting common do-file errors.
  • Learn common routines for cleaning, importing and merging data; generating, recording and labeling variables; and generating descriptive data tables and plots.

Day 8 06/01

Automating Common Tasks in Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Demonstrate how Stata's pre-canned capabilities can be extended to user-written ado-files.
  • Learn to write code to automate data cleaning, organization and analytic tasks.
  • Introduce simple code to download data from the web using Stata.

Day 9 06/02

Data Visualization in Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Review Stata's pre-canned programs for creating plots, charts, and graphs. 
  • Introduce common syntax for customizing graphics using Stata's suite of graphing commands.
  • Learn to use Stata's "margins" and "marginsplot" commands for visualizing regression results.

Week 3 - Structural Equation Modeling. Watson Library, Room 455

 

Day 10 06/05

Introduction to Structural Equation Modeling

Instructor: Dr. Edgar Merkle, University of Missouri, Department of Psychological Sciences

  • Factor Analysis Overview
  • Confirmatory Factor Analysis By Example
  • Visualizing SEM with path diagrams
  • Diagnostics for Estimated Models

Day 11 06/06

Using Mplus and R

Instructor: TBA

  • Introducing the CRMDA SEM Code Repository
  • Mplus
  • Using R for basic SEM: the lavaan package

Day 12 06/07

Interaction Effects in SEM

Instructor:  Dr. Holger Brandt, Dept. of Psychology, KU

  • lavaan overview
  • Product Indicators
  • The R package nlsem
  • Latent moderate structural equations (LMS)
  • Graphical illustrations

Day 13 06/08

Extensions to semiparametric approaches

Instructor:  Dr. Holger Brandt, Dept. of Psychology, KU

  • Structural equation mixture modeling (SEMM)
  • SEMM with the R packages nlsem and plotSEMM
  • Robust alternatives for nonnormality
   

Day 14 06/09

Bayesian alternatives and multilevel SEM

Instructor:  Dr. Holger Brandt, Dept. of Psychology, KU

  • (Short) introduction to Bayesian modeling
  • Introduction to stan (a Bayesian analysis framework) and rstan (an R package for usage of stan)
  • Interaction models with regression and the multilevel framework in stan
  • Multilevel SEM with interaction effects in stan
Please Enroll as soon as possible.  Space is limited

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