May 9 - May 10$650 – $850
This two-day hands-on workshop covers various topics in multilevel modeling with continuous and categorical variables. More specifically, we will cover:
- Concepts of growth modeling
- Unconditional growth models
- Centering points and non-linear terms
- Growth modeling with covariates
- Advanced growth models
- Modeling heterogeneity
- Missing data
- Power analysis
Syntax and output for both Mplus and R will be provided for all examples covered in the workshop.
You will find information regarding the workshop below. Registration and payment can be made directly online. We accept PayPal, Visa, MasterCard, American Express, Cheques and Email Transfers.
We offer discounted pricing for graduate students and post-doctoral fellows.
|Time||Day 1||Day 2|
|9:00 - 9:30||Welcome and overview||Review of previous day|
|9:30 - 10:30||1. Concepts of Growth Modeling - Common methods for analyzing longitudinal data - Growth trajectories - Parts of a growth model - Data requirements, model identification, and model fit||5. Advanced Growth Models I - Two-part models - Parallel process models - Examples with continuous and categorical data|
|10:30 - 11:00||Break||Break|
|11:00 - 12:00||2. Unconditional Growth Models - Growth models without covariates - Plotting trajectories - Examples with continuous and categorical data||6. Advanced Growth Models II - Autoregressive latent trajectory (ALT) - Moderators in ALT models - Examples with continuous and categorical data|
|12:00 - 1:00||Lunch||Lunch|
|1:00 - 2:30||3. Centering Points and Non-Linear Terms - Fixed versus individual varying time scores - Quadratic growth models - Examples with continuous and categorical data||7. Modeling Heterogeneity - Multiple group growth modeling - Latent class growth modeling - Examples with continuous and categorical data|
|2:30 - 3:00||Break||Break|
|3:00 - 4:30||4. Growth Modeling with Covariates - Time invariant covariates - Time varying covariates - Examples with continuous and categorical data||8. Missing Data and Power Analysis - Handling missing data - Power analysis for sample size estimation - Examples with continuous and categorical data|
|4:30 - 5:00||Wrap-up||Wrap-up|
This workshop is for anyone interested in learning how to deal with longitudinal data within a growth modeling framework. Participants are encouraged to have a working knowledge of multiple regression and an advanced understanding of structural equation model (see our Advanced Structural Equation Modeling workshop here).
No prior knowledge of Mplus or R is required.
For this hands-on workshop we will be working with both Mplus and R using R-Studio. For those who are not working with any specific software, we provide all syntax and output for each example to allow for participation without the use of any software.
If you do not own a copy of Mplus, a free but limited demonstration version is available for download at the Mplus Website. To run all of the examples used during the workshop, it is recommended that participants have a licensed copy of the Mplus Base program with the Mixture Add-On or the Combination Add-On. The R software is available as a free download here, and the R-Studio software can be downloaded for free here.
Handout materials and datasets will be provided.
A continental breakfast will be served at the beginning of each day. Coffee/tea and light snacks will be provided at each break. A light lunch (including vegetarian and gluten free options) will be provided each day. For those who wish to explore other dining options, there are plenty of restaurants in the area.
Located in beautiful downtown Toronto, Ontario, Canada, the workshop will be held at 141 Adelaide Street West, 16th Floor, Suite 1670.
If you are coming via GO Train or TTC, go to Union Station and take the Yonge-University line (North) to St. Andrew Station. Walk one block north (140 metres) on University Avenue and then turn right on Adelaide Street West. The building will be on your right (south side) on the corner of Adelaide Street West and York Street. You will find a map of the Toronto subway system here.
If you are coming by car, there are a number of parking lots within walking distance. The closest lot is an Impark Parking lot at 150 King Street West, Toronto which is open 24 hours. Further information may be found here. Alternatively, if you don't wish to drive downtown, you could park at a subway station and take the subway. You will find a list of subway stations with parking here.
If you are coming from Toronto Pearson International Airport, the Union Pearson Express will take you from the airport to downtown Toronto in 25 minutes and runs ever 15 minutes from 5:30am to 1:00am. See the Union Pearson Express website for more information and to purchase travel tickets.
There are a number of hotels below (with links) within a 10-15 minute walk from the workshop location.
Delta Hotels by Marriott Toronto (12 min walk) 75 Lower Simcoe Street Toronto, Ontario, M5J 3A6 Phone: (416) 849-1200
Fairmont Royal York (7 min walk) 100 Front Street West Toronto, Ontario, M5J 1E3 Phone: (416) 368-2511 Toll Free: (866) 540-4489
Hilton Toronto (3 min walk) 145 Richmond Street West Toronto, Ontario, M5H 2L2 Phone: (416) 869-3456
Hotel Le Germain Maple Leaf Square (10 min walk) 75 Bremner Boulevard Toronto, Ontario, M5J 0A1 Phone: (888) 940-7575
InterContinental Toronto Centre (9 min walk) 225 Front Street West Toronto, Ontario, M5V 2X3 Phone: (877) 660-8550
Sheraton Centre Toronto Hotel (4 min walk) 123 Queen Street West Toronto, Ontario, M5H 2M9 Phone: (416) 361-1000
The Strathcona Hotel (4 min walk) 60 York Street Toronto, Ontario M5J 1S8 Phone: (416) 363-3321
Scott Colwell, PhD is an associate professor at a major university in Ontario and is the co-founder of Enablytics. He has many years of experience teaching courses and workshops in research methods, applied statistics, and structural equation modeling to students from a variety of social, behavioural and health science disciplines. Dr. Colwell is an accredited Chartered Statistician (CStat®) with the Royal Statistical Society and Professional Statistician (PStat®) with the American Statistical Association. Additional information can be found here.
Registration will continue until the workshop begins. If you need to cancel your registration, please contact us at firstname.lastname@example.org.
Cancellations up to 30 days prior to the event will be refunded at 100%. Cancellations between 11 and 29 days prior to the event will refunded at 50%. There are no refunds for cancellations made 10 days before the event begins. Should you need to cancel your registration please keep in mind that we do not cancel any other arrangements you have made such as hotel accommodations. If you registered by credit card, a 5% transaction fee will apply to any cancellation.
You may transfer your registration to another individual for free by contacting us at email@example.com.