Missing Data Analysis with Longitudinal Data
May 11 @ 9:00 am - 5:00 pm$250
We are pleased to offer this new one-day hands-on workshop covering missing data analysis for longitudinal data. More specifically, we will cover:
- Review of longitudinal modeling
- Conceptual overview of missing data
- Testing missing data mechanisms
- Traditional approaches to MCAR and MAR
- Better approaches to MCAR and MAR
- Dealing with missing not at random (MNAR)
Syntax and output for Mplus 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.
For this inaugural offering we are providing this workshop for $250 (Canadian) for all interested participants.
|9:00 - 9:15||Welcome and overview|
|9:15 - 10:00||1. Review of Longitudinal Data Modeling - Wide versus long data - Growth modeling approaches to longitudinal data - Multilevel modeling approaches to longitudinal data|
|10:00 - 10:30||2. Conceptual Overview of Missing Data - Missing data patterns - Missing data mechanisms|
|10:30 - 10:45||Break|
|10:45 - 12:00||3. Testing Missing Data Mechanisms - Testing for missing completely at random (MCAR) - Testing for missing at random (MAR) - Testing for missing not at random (MNAR)|
|12:00 - 1:00||Lunch|
|1:00 - 2:00||4. Traditional Approaches to MCAR and MAR - Listwise deletion - Pairwise deletion - Missing indicator - Single imputation|
|2:00 - 3:00||5. Better Approaches to MCAR and MAR - Multiple imputation - Maximum likelihood and FIML|
|3:00 - 3:15||Break|
|3:15 - 4:30||6. Dealing with Missing Not At Random - Selection models (Diggle-Kenward 1994 and Wu & Carroll 1998) - Patern mixture models (Conventional pattern-mixture model and Roy's latent class dropout model)|
|4:30 - 5:00||Review and Wrap-up|
This workshop is for anyone interested in learning how to deal with missing data when using longitudinal data. Participants are encouraged to have a working knowledge of multiple regression and an understanding of growth modeling (see our Growth Modeling workshop here).
No prior knowledge of Mplus is required.
For this hands-on workshop we will be working with Mplus. 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 Combination Add-On.
Handout materials and datasets will be provided.
Coffee/tea and light snacks will be provided at each break. Lunch will not be provided however, 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 email@example.com.
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 firstname.lastname@example.org.