Bayesian estimation is becoming increasingly popular and necessary for answering complex research questions. In this first, of the two part Introduction to Bayesian Analysis workshop series, we provide a very practical introduction to Bayesian estimation. Topics Include:

  1. Why Bayesian and why now
  2. Understanding the concepts of Bayes
  3. Estimating parameters using Markov Chain Monte Carlo (MCMC)
  4. Model fit

During this five-hour workshop, examples will be demonstrated using the Mplus software. However, our focus will be more on the conceptual understanding rather than the software. Materials, syntax (for both Mplus and R), and Mplus output will be provided for all examples, so it is not necessary to have the Mplus software to participate.

We offer discounted pricing for graduate students and post-doctoral fellows as well as discounts for multiple registrations. Registration and payment can be made directly online. Price is exclusive of tax. We accept Visa, MasterCard, American Express, Cheques and Email Transfers.

PRICE
Student / Post-Doc
$325.00
Standard
$425.00
SCHEDULE
  1. A motivating example
  2. Benefits of Bayes
  3. Terminology
  4. Software considerations
  1. Prior, likelihood, and posterior distributions
  2. Bayes theorem
  3. Comparing maximum likelihood and Bayes estimation
  1. Model Convergence
  2. What is Markov Chain Monte Carlo (MCMC)
  3. Mixing and Burn-in
  4. Trace Plots
  5. Autocorrelation Plots
  1. Posterior predictive checking (PPC)
  2. Posterior predictive p-value (PPP)
  3. Deviance information criterion (DIC)
  4. Example with simple mediation
F.A.Q.

This workshop is for anyone interested in gaining a very introductory understanding Bayesian analysis.

Participants are encouraged to have a working knowledge of multiple regression. No prior knowledge of Mplus or R is required.

During this five-hour workshop, examples will be demonstrated using the Mplus software. However, our focus will be more on the conceptual understanding rather than the software.

Materials, syntax (for both Mplus and R), and Mplus output will be provided for all examples to allow for participation without the use of any software.

While software is not required for this workshop, you will find the Mplus software here, the R software here, and the R-Studio software here.

Registration will continue until the workshop begins. If you need to cancel your registration, please contact us at info@enablytics.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 info@enablytics.com.

INSTRUCTOR

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 (CStatĀ®) with the Royal Statistical Society and Professional Statistician (PStatĀ®) with the American Statistical Association.

LIVESTREAM

A link and passcode to the livestream will be sent to all registered participants prior to the start of the event.
Materials will be made available for participants online for download.

Please note: We currently do not have the ability to record the streaming.

CONTACT

    Event Details