Introduction to Bayesian Analysis using Mplus

Date:

24/08/2016

Organised by:

Falcon Training / Figure It Out

Presenter:

Dr Chris Stride

Level:

Intermediate (some prior knowledge)

Contact:

Chris Stride 07952210227
bookings@figureitout.org.uk

Map:

View in Google Maps  (WC1E 7HX)

Venue:

Birkbeck College, London

Description:

Introduction to Bayesian Analysis using Mplus

This course is promoted by Falcon Training

Who is the course aimed at?
This course is aimed at those with previous knowledge of Mplus who wish to use the software as a way into the world of Bayesian estimation. As such it is an ideal follow on course for individuals or groups who have previously taken our introductory course in Structural Equation Modelling, or as a the second day of a two-day inhouse course, with the first day being the introductory course in Structural Equation Modelling.

Course level:
A basic knowledge of the Mplus language (reading data in, running files, the BY, ON, WITH commands, and the use of @ and ( ) symbols for fixing and naming parameters), and how path analysis models and model improvement are tested e.g. basic fit indices, chi-square tests) is required. It is also highly desirable to have an understanding of basic and intermediate level statistical methods, specifically t-tests, anova, simple linear regression, logistic regression, and CFA, since we will cover using Bayesian estimation in all of these methods. No previous knowledge or experience with Bayesian estimation is assumed.

Course content and aims:
The course will cover the following topics:

  • What is Bayes Theorum and how can it help us?
  • Bayesian estimation vs classical statistics/null hypothesis significance testing
  • Selecting appropriate 'priors'
  • Using Monte Carlo Markov Chains for model fitting
  • Using Bayesian estimation to fit a simple linear regression model in Mplus
  • Using Bayesian estimation to fit a path analysis model in Mplus, including estimating indirect effects
  • Using Bayesian estimation to fit a CFA in Mplus

    The course comprises of a mixture of short lectures on the basic theory behind Bayes theorum, Bayesian estimation, and Monte Carlo Markov Chain (MCMC) methods, teaching via examples worked through by the trainer on real data sets which participants can follow, and exercises to practice the skills just learned. You will also receive a 80-page coursebook containing all the notes and worked examples, providing an easy reference for the basics of performing Bayesian Estimation in Mplus, and as a reminder for the techniques you have learned.

    Course schedule: The course will start at 9.00am, with a lunch break from 12.30pm-1.30pm, and short coffee breaks at 11.00am and 3.30pm. It will finish at around 5.15pm, though I will be willing to stay on for a while after this to answer questions pertinent to participants' own data sets.

    The teacher:
    Dr Chris Stride has been using MPlus in his work as a statistician and data manager for the last decade. He has particular experience and expertise in teaching non-statisticians from the fields of psychology, HR, management and the social sciences. Chris is a Chartered Statistician and a member of the ASSESS (UK SPSS Users' Group) Committee; and has run almost 100 public training courses around the world, as well as for the UK SPSS users group, at national and international conferences, and on an inhouse basis for Universities and the public sector.

Cost:

£225 waged / £175 students. Further discount for booking multiple courses

Website and registration:

Region:

Greater London

Keywords:

Measurement Error, Bayesian methods, Markov Chain Monte Carlo (MCMC), Regression Methods, Linear regression, Latent Variable Models, Confirmatory factor analysis, Structural equation models, Quantitative Approaches (other), Quantitative Software, Mplus, Winbugs, ICT and Software (other), Bayesian Analysis , Bayesian Estimation , Prior Probability , Posterior Probability

Related publications and presentations:

Measurement Error
Bayesian methods
Markov Chain Monte Carlo (MCMC)
Regression Methods
Linear regression
Latent Variable Models
Confirmatory factor analysis
Structural equation models
Quantitative Approaches (other)
Quantitative Software
Mplus
Winbugs
ICT and Software (other)

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