2018 CRMDA Stats Camp: Summer Statistical Institute

Graduate students, faculty, staff, government agencies, corporations and others are invited to attend the KU Stats Camp. CRMDA is offering three weeks of sessions about R, Python Data Science and Structural Equation Modeling. KU Stats Camp begins the last week of May and continues into the first two weeks of June. 

Registration is Closed

If you are interested in attending, please contact CRMDA at crmda@ku.edu.

Can't attend in person? Attend remotely using Zoom!

If you are a student, faculty member or staff at KU, go to kansas.zoom.us to access your account. If you are not affiliated with KU, Zoom is a free web conferencing service. To sign up for an account, go to zoom.us.

Hotel/Housing Info

CRMDA refers guests to the Double Tree by Hilton (special rate: $99/night). To receive the special rate, call 785-841-7077 by May 11th and say you are with the CRMDA group. We also refer guests to the Halcyon House Bed & Breakfast. Guests can call 785-841-0314 and inquire about the KU rates. There is also a limited number of rooms in KU Guest Housing. Space will be filled on a first-come-first-served basis. Nightly rates are $55 to $70. Visitors who intend to stay in campus housing MUST check-in between 3 p.m. and 5 p.m. and MUST check out by 10 a.m. The Student Housing Office is located at Corbin Hall, 422 W 11th St., Suite DSH and is open from 8 a.m. to 5 p.m., Monday-Friday. Reservations must be made through the CRMDA offices. Please email crmda@ku.edu or call 785-864-3353 to arrange accommodations. 



Our sessions are on the main campus of KU. Weekly parking passes at $22/week are available from the KU Parking Department located in the Allen Fieldhouse Garage on the 3rd level (1501 Irving Hill Road, Lawrence, KS 66045). This would allow guests to park in any unmarked stall in Gold, Blue, Red, or Yellow lots. To obtain a pass, it is necessary for visitors to go to the Parking office. They are open from 7:30 a.m. to 5:00 p.m. Monday thru Thursday and close at 4:30 p.m. on Fridays. The Parking office recommends visitors call ahead (785-864-7275) so the paperwork and payment is completed in advance. Tell them you are with the CRMDA Summer Statistical Institute to receive the reduced price for a weekly pass.


CRMDA 2018 Summer Institute Course Descriptions

Sessions daily 9 a.m. - 12 p.m. & 1:30 p.m. - 4 p.m.

Week 1: R. Wescoe Hall, Room 4066 (EGARC: Ermal Garinger Academic Resource Center)

Day 1 05/21

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 05/22

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 05/23

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 05/24

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 05/25

Monte Carlo Programming & Power Analysis

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

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


Week 2 - Topic: Python Data Science, Watson Library, Room 455

Day 1 05/29

Getting Started in Python

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • What is Python?
  • Installing Python and Anaconda
  • Navigating around Jupyter Notebooks
  • Discuss basic features and functions of Python

Day 2 05/30

Working with Text Data

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • Work with texts and the question of data
  • Introduce National Language Toolkit (NLTK)
  • Discuss key functions and basic text analysis using NLTK
  • ​Advanced Text Analysis, Corpus Analysis and Sentiment Analysis
  • Topic modeling and measuring document similarity

Day 3 05/31

Data Science

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • Introduce Pandas
  • Discuss various functions of Pandas
  • Perform statistical analysis

Day 4 06/01

Working with Internet Data

Instructor: TBD

  • Scrape data from the Internet
  • Understand web data formats
  • Turn webpages into datasets
  • Analyze Internet datasets

Week 3 - Topic: SEM, Watson Library, Room 455


Day 1 06/04

Introduction to Structural Equation Modeling

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

  • From Regression to SEM
  • Confirmatory Factor Analysis
  • Estimation and Evaluation
  • Advanced Topics: Multiple groups, Measurement Invariance

Day 2 06/05

Creating Models and Fitting Them (Part 1)

Instructor: CRMDA Staff

  • Brief R Overview, including the bootstrap
  • Estimating SEM with the lavaan package
  • Moderators and Mediators in SEM
  • The SEM Example Collection: Overview
  • The Examples fitted with lavaan
  • Acceptable Tables: The CRMDA semTable package

Day 3 06/06

Creating Models and Fitting Them (Part 2)

Instructor: CRMDA Staff

  • Introduction to Mplus
  • ​Ordinal Logistic Regression
  • SEM with Ordinal Data
  • Problems associated with Chi-Square Difference Tests

Day 4 06/07

Dealing with Missing/Incomplete Data

Instructor: CRMDA Staff
  • The Problem of Missing Data: Listwise deletion is especially harmful in SEM
  • FIML as a remedy for incomplete data
  • No FIML for Ordinal Models? What Now?
  • Multiple Imputation

Day 5 06/08

The New Wave: Bayesian Models for Structural Equations

Instructor: CRMDA Staff

  • Bayesian Perspective
  • Specifying SEM for Bayesian Estimation
  • Examples from competing software (BUGS/JAGS and Stan)

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