The Quantitative Research Methods Training Unit (QRM-TU) offers a series of training session which aim to develop the knowledge, understanding and skills necessary to specify, test, and interpret latent variable statistical models and propensity score matching techniques. All courses are held at the University of Huddersfield and there are places for a maximum of 20 participants per course.

The courses are delivered by means of lectures and practical sessions. All analyses are conducted under supervision of the lead instructor and three tutors to maximise learning outcomes (we offer a 1:5 instructor student ratio). Each course concludes with a question and answer session, and there is always the opportunity for participants to discuss their own studies with the tutors.

Course title

Confirmatory Factor Analysis using Mplus (CFA, Bifactorial Modelling, Test for Factorial Invariance)

Structural Equation Modelling using Mplus and Amos, (SEM, Mediation Analysis within SEM framework, Path Analysis)

Latent Growth Analysis using Mplus and Amos

Latent Class Analysis using Mplus

Propensity Score Analysis using R (greedy matching and full matching techniques, post-matching multivariate analysis)

Propensity Score Matching and Structural Equation Modelling using R

Moderation Analysis using SPSS (Moderated Logistic and Multiple Regression)

 

 

If you would like to enquire further about the courses offered by the QRM-TU contact:
Dr Daniel Boduszek
E-mail: d.boduszek@hud.ac.uk

Upcoming courses in September 2018

Regression and Moderation Analysis in SPSS (linear and logistic regression, moderation analysis, SPSS, Modgraph) - 2 days

Systematic Reviews and Meta-Analysis – 1 day

 

Propensity Score Analysis using R (greedy matching and full matching techniques, post-matching multivariate analysis) – 2 days

 

A Complete Beginner’s Course to Bayesian Analysis - 1 day

 

Introduction to Confirmatory Factor Analysis and Structural Equation Modelling using Amos & Mplus, (CFA, SEM, Mediation Analysis within SEM framework, Path Analysis) – 3 days