CARMA Live Online Short Courses 

Australia Region

Sponsor

April 20-24, 2020 – Two Sessions, Two Courses

Sponsored by University of South Australia

Session 1: April 20-22 | Session 2: April 22-24

We offer two sessions which allows course participants the opportunity to take two back-to-back courses.

Session 1

Monday April 20 (all day), Tuesday April 21 (all day), and Wednesday April 22 (AM half day)

Session 2

Wednesday April 22 (PM half day), Thursday April 23 (all day), and Friday April 24 (all day)

CARMA Workshop: Basics of R

This four-hour Workshop provides information on the package R to prepare attendees for follow-up training in CARMA Short Courses that use R. By attending this online workshop, participants will learn basic skills for using the R Studio interface to: load and activate R packages, import and manage data, and create and execute syntax. Having these basic skills will allow Short Course participants to more easily learn about use of R for data analysis and will enable Short Course instructors to better plan and deliver their content. This Workshop is only available to those who will be attending one of the CARMA Short Courses. It will be available on-line.

During this Basics of R Workshop, attendees will learn:
1. Using R through the R Studio interface
2. Importing data into R
3. R data sets (a.k.a data frames and tibbles)
4. Data types
5. Subsetting columns of data and selecting cases
6. Recoding data and dealing with missing data
7. Merging data (columns and rows)
8. Output objects
9. User defined functions
10. Getting help

“Introduction to Multilevel Analysis with R” – Dr. James LeBreton, Pennsylvania State University

Course Description

The CARMA Introduction to Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct basic multilevel analyses. Emphasis will be placed on techniques for traditional, hierarchically nested data (e.g., children in classrooms; employees in teams). The first part of the course introduces issues related to multilevel theory (e.g., multilevel constructs; principles of multilevel theory building; cross-level inferences and cross-level biases). The second part of the course discusses issues related to multilevel measurement (e.g., aggregation; aggregation bias; composition and compilation models of emergence; estimating within-group agreement). The last part of the course focuses on the specification of basic 2-level models (e.g., children nested in classrooms; soldiers nested in platoons; employees nested within work teams) analyzed via multilevel regression (i.e., random coefficient regression; hierarchical linear model; mixed effects model). The R software package will be introduced, explained, and emphasized during this short course in preparation for the advanced short course offered in Session II. Participants who prefer HLM, SAS, SPSS, or MPlus (and have expertise with these programs) have the option of completing some assignments with these programs. Participants are encouraged to also bring datasets to the course and apply the principles to their specific areas of research. The course is best suited for faculty and graduate students who are familiar with traditional (i.e., single-level) multiple regression analysis, but have little (if any) expertise related to conducting multilevel analyses.

  • Module 1: Multilevel Theory: Constructs, Inferences, and Composition Models
  • Module 2: Multilevel Measurement: Aggregation, Aggregation Bias, & Cross-Level Inference
  • Module 3: Multilevel Measurement: Estimating Interrater Agreement & Reliability
    • Examples using R
    • Examples using SPSS Software (time permitting)
  • Module 4: Multilevel Measurement and Multilevel Modeling: A Simple Illustration of Analyzing Composite Variables in Hierarchical Linear Models
    • Examples using R
    • Examples using SPSS Software (time permitting)
  • Module 5: Review of the 2-Level Model and Final Q & A
  • Other topics (only if time permits) might include:
    • Extension of the 2-level model to the study of growth and change (i.e., growth model)
    • Different centering/scaling stragies (e.g., group-mean centering vs. grand-mean centering)

Required Software: R (download here), RStudio (download here)

“Advanced Multilevel Analysis with R” – Dr. Paul Bliese, University of South Carolina

Course Description

The CARMA Advanced Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct more advanced multilevel analyses. Emphasis will be placed on techniques for longitudinal data. The R software package will be introduced, explained, and used throughout this short course. The topics covered in this course include specifying and analyzing basic, 2-level, models (e.g., individuals nested in teams; repeated observations nested in individuals), as well as, more advanced 3-level models (e.g., individuals nested in teams that are nested in organizations; repeated observations nested in individuals that are nested in teams). Other topics include: multilevel mediation and the analysis of dyadic data. Exercises using real-world data, are conducted in R. Participants who prefer HLM, SAS, SPSS, or MPlus (and have expertise with these programs) will have the option of completing some assignments with these programs. Participants are encouraged to also bring datasets to the course and apply the principles to their specific areas of research. The course is best suited for faculty and graduate students who have at least some foundational understanding of issues related to multilevel data and how to analyze simple, 2-level, models.

    • Module 1: 2-Level Mixed Models: Cross-Level Main Effects & Interactions
      • Examples using R
    • Module 2: Analyzing Change and Growth: 2-Level Growth Model
      • Examples using R
    • Module 3: 3-level Models
      • Examples using R
    • Module 4: Multilevel Mediation
      • Examples using R
    • Module 5: Analyzing Dyadic Data
      • Examples using R
      • Other topics (only if time permits) might include:
        • Multilevel Models for Non-Normal Outcome Variables
        • Bayes Estimates in R
        • Discontinuous Growth Models

Required Software: R (download here), RStudio (download here)

Registration, Pricing, Advanced Registration Deadline and Time Schedule

To register for 2020 CARMA Live Online Short Courses, you must first log in to your CARMA account (If you do not already have an account, please sign-up as a website user). Once you have logged in, and you are in the User Area, select “Purchase Short Course” on the right side of the page.

Pricing Dates * CARMA
Member **
Non-CARMA
Member
Prof. Assosication Member
(AOM,SIOP,SMA,AAOM,   IACMR,EURAM,EAWOP,AIB, ANZAM,INDAM) ****
1 Course 2 Courses *** 1 Course 2 Courses *** 1 Course 2 Courses ***
Advanced Registration
03/19/2020 – 04/01/20
Faculty $425 $750 $850 $1,600 $680 $1,260
Advanced Registration
03/19/2020 – 04/01/20
Student $325 $550 $650 $1,200 $520 $940
Normal Registration
04/02/20 – 04/15/20
Faculty $475 $850 $950 $1,800 $760 $1,420
Normal Registration
04/02/20 – 04/15/20
Student $375 $650 $750 $1,400 $600 $1,100

* – To receive these prices, you must complete your registration during the dates specified.

** – These prices reflect a 50% discount that you receive if you are student/faculty at an organization that is a member of the CARMA Institutional Premium Membership OR the CARMA Institutional Basic Membership Program.

*** – These prices reflect a discount in which you register for 2 courses and receive $100 off.

****–These prices reflect a 20% discount for members of following associations; Academy of Management (AOM), Southern Management Association (SMA), Society for Industrial and Organizational Psychology (SIOP), Asia AOM (AAOM), International Association for Chinese Management Research (IACMR), European Academy of Management (EURAM), European Association of Work and Organizational Psychology (EAWOP), Academy of International of Business (AIB), Australia and New Zealand Academy of Management (ANZAM), and Indian Academy of Management (INDAM). This discount can not be applied if you are also using CARMA membership discount.

If you are a member of AOM, SIOP, SMA, AAOM, IACMR, EURAM, EAWOP, AIB, ANZAM, and INDAM, you can use one of the following discount codes when registering for these short courses:

Faculty Code: 4bb9-ec55
Student Code: 13bf-d354

Note that we will be verifying association membership for all those who use these discount codes. Anyone who uses one of these discount codes and is not a member of those associations will be required to pay the non member rate.
If your organization is not yet a member but would like to become one, please contact us directly at carma@ttu.edu.

All participants are eligible for the following discount:
Register for both sessions, receive $100 off the total price.

Refund Policy: Full refund will be provided up to 2 weeks before the first day of the session. After that date, partial refund (50%) will be provided.

Time Schedule

Sponsor, University of South Australia
Session 1 (April 20-22) Session 2 (April 22-24)
Location Monday Tuesday Wednesday Wednesday Thursday Friday
Adelaide 8 AM- 3 PM 8 AM- 3 PM 8 AM- 11 AM 12 PM -3 PM 8 AM- 3 PM 8 AM- 3 PM

For the time schedule of different countries/cities click here.