Learn SEM with Mplus in Cambridge

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Learn SEM with Mplus in Cambridge

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Learn SEM with Mplus in Cambridge

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Learn SEM with Mplus in Cambridge

Feel the history of the place.


Since 2013, I’ve been delivering courses on Structural Equation Modelling (SEM) with Mplus here in Cambridge, first under the umbrella of the University of Cambridge and since 2017, as a private (ad)venture. I love it! And I think you will love it too, as we have worked very hard on delivering a really nice experience (yes, that means there’s lots of cake every day).  🙂

The courses are hosted at one of the Cambridge University colleges: Selwyn College. Having the course hosted at a College means you will also get to experience the uniqueness and charm of the Cambridge Collegiate system. And I am particularly excited about having Selwyn College as our host because the entire college site looks like a fairy-tale!


This 3 day course has been exceptionally well delivered by an active researcher who is extremely knowledgeable, patient and thoughtful to the needs of the audience. I particularly enjoyed the blend between lecture material and practical skills development using MPlus, supported by excellent handout material and supporting electronic files. I would highly recommend this course to anyone who is new to MPlus.

Prof Neil Coulson, University of Nottingham, UK

Honestly, I loved it. If someone asked me if I would recommend the experience I would say yes, definitely. I started without any knowledge about Mplus and in just three sessions I came out with many ideas to apply to my own research. I think the organization of the course was perfect. The explanations were always clear, with numerous examples. A subject as arduous as statistics was easy to understand. To this also contributed the fact that they made breaks every hour and quarter!

Dr Carlos Freire, University of A Coruña, Spain

This is the best course I have ever taken – Gabriela makes these complex and advanced techniques simple and easily digestible, prepare to learn a great deal and have a lot of fun doing it!

Joanna Davies, UCL, UK

Thank you so much for all. Its been a great experience having the opportunity to participate in the course. It was really helpful  to me. You are so clear at teaching and make statistics seem  easier! I’ll definitely recommend the training to others.

Dr Monica Guzman, Universidad Catolica de Norte, Chile

It was so incredibly helpful and I actually feel as though you gave me a very important gift in my career.  I have many skills as a researcher but never saw complex methods as something that would be accessible to me.  I had always seen statistics as something to be feared and struggled with but your course actually gave me the most wonderful enthusiasm and excitement about working with my data.  It’s made me so much more confident going forward and I will be forever grateful for that.  I have had so many ideas since your course that it’s hard to focus on just one.

Kirsten Smith, University of Oxford, UK

This MPlus course was fantastic. It not only provided me with the skills and confidence to conduct the analyses in MPlus but, also, the details of why, how, and what the analyses were about. Furthermore, I now know how to read and interpret the output files to assess and modify my models.

Dr Melissa Scarpate, University of Cambridge, UK

I attended the Structural Equation Modeling with Mplus course this autumn and found it very helpful. Gabriela explains and illustrates statistical models and Mplus programming in ways that ensures understanding, practical knowledge, and interpretation of the results. Her pedagogical ways in teaching are extraordinary and she explains difficult topics very well and ensures integrated understanding from the audience. The course, with good theoretical introductions and examples, ensures that every participant will progress in practice and understanding throughout the course.

Dr Rolf Gjestad, University of Bergen, Norway

Mplus course in Structural Equation Modelling (SEM) is truly unique. The course offers important topics about SEM and factor analysis that are all taught by a wonderfully supportive instructor who made me love statistics, even more; especially that it was not taught in a technical way. All the examples that were used made it easy to understand the statistics behind it. I wholeheartedly recommend it to anyone who is interested in statistics and looking to gain the essential skills needed for their academic careers, including graduates and researchers from different fields.

Eman El Sahan, University of Cambridge, UK

I did three courses in SEM in different UK universities last year, and this is by far the best. This course is pragmatic, it teaches you what you need without dwelling into complex mathematical explanations but at the same time, the basics are covered so you can be confident you will do your analysis rigorously.

Dr Blanca Bolea, University of Bristol, UK

The Mplus course is practical oriented. Many useful and helpful examples are provided in a cooperative atmosphere. And I really enjoyed the group atmosphere of the course.

Amelie Rogiers, Ghent University, Belgium

Attending the course turned out to be the best decision I ever made. The course has indeed provided me with the knowledge and skills necessary to analyze my data and turn them into meaningful causal models. Advanced topics such as mixture modeling, which I thought I’d never ever grasp, was made very simple. In sum, the course was awesome and enjoyable and I would highly recommend it.

Amna Al Abri, University of Conneticut, USA

Before starting on the course I didn’t know anything about SEM or MPlus. By the end of the course I felt confident enough to try these techniques on my own data. It was a very supportive and flexible course taught by a very knowledgeable tutor.

Dr Fiona Kyle, London City University, UK

The most useful course I went to. If you want to start working with Mplus, I strongly recommend taking this course. Everything is right: the pace, the reasonable size of the group, the theory kept to a bearable amount and the multiple applications and examples to get hands on the data analysis straight away. Gabriela makes sure everyone follows and is not stuck before moving on, so that we actually learn and apply the new knowledge straight away. I started using Mplus for longitudinal data analysis (latent growth curve modelling) for my own research after the course and the course material is my bible – I am referring to it all the time!

Dr Camille Lassale, UCL, UK

I really enjoyed the Mplus course. You don’t feel left behind, as it is practical and hands-on. I did not know a thing about Mplus nor SEM before I started the course and now I was already able to use some of the techniques on my own data…with success!

Mona De Smul, Ghent University, Belgium

This MPlus course with Gabriela was a great experience! It offered me a profound theoretical basis on SEM together with a lot of useful tips-and-tricks to work on my own data. Gabriela’s enthusiasm really encouraged me and she managed to explain complex ideas in a really comprehensible way. I would recommend this course to anyone interested in MPlus!

Sofie Heirweg, Ghent University, Belgium

I recently attended the structural equation modeling course run by Dr Gabriela Roman at Cambridge University. It was an instant relief to be a part of this course since I knew I would be using SEM for one of my PhD chapters but had no prior knowledge of this technique, and the course was run at a very comfortable pace, it was highly comprehensive and enjoyable. I benefitted very much, taking away with me invaluable knowledge of the basic foundations of SEM as well as insight into the intricacies of actually running these models and dealing with common and unusual problems- the latter of which I have been very grateful for recently when working with my own data! I highly recommend anyone who will be working with SEM to attend this course, it was excellent.

Ada Miltz, UCL, UK

This is a course that you should take, no matter whether you studied SEM before or not, or whether you used Mplus before or not. The scope of the topics covered in this course caters for pretty much every SEM researcher.

Ali Al Hoorie, UCL, UK

The course is very useful; the clear instruction explains how to trouble shoot difficulties in Mplus, leaving students confident at approaching future analysis.

Hanna Creese, UCL, UK

Gabriela’s course is unique in being taught by a real statistics expert who can answer any question you can imagine. The fact that she can also teach the basics with clarity makes this class highly valuable.

Peter Ward, University of Warwick, UK


The University of Cambridge is a “collegiate” university and is composed of Faculties, Departments and Colleges. As such, the Colleges are integral to the make-up of the University. Indeed, when students apply for a Bachelor’s degree, their application is evaluated by one or more colleges and they are admitted by a college, rather than a department. Furthermore, teaching for undergraduates contains two components: lectures and supervisions. Lectures are delivered at the department. Supervisions, which are small-group teaching sessions, are arranged and delivered by the colleges. They accompany broad-brush lectures and are regarded as one of the best teaching models in the world. Each college has its unique features and history.

Selwyn College, where our course will take place, was one of the first in Cambridge to go mixed, admitting women in 1976. The distinctive red-brick Victorian Old Court is Tudor Gothic in style, much of it designed by architect Sir Arthur Blomfield.

Do you wish to stay at the College? The College rooms are all single en-suite and include breakfast. To book a room, use these 3 steps procedure:  click here, then add the code SEM2022 in the Promo field, then check the room availability. It is important that you include the promo code before you check availability, as otherwise the website will show no room availability.


This course is a data analysis course, not a statistics course. What does this mean? It means we will learn when to use different statistical techniques based on our research questions, what these techniques do (in an intuitive non-mathematical way), how to apply them using Mplus and how to interpret the results. As this course is non-mathematical, it is aimed at complete beginners, so you don’t need to have any prior knowledge of either SEM or Mplus.

You will need to bring a laptop that has the demo version of Mplus installed (you can download that free of charge from statmodel.com). Please be aware that to do your analyses, it is not likely that the demo version will suffice. If you don’t yet have Mplus, it is best to come to the course first and then buy the software license, as the course will help you choose the correct version for your research needs.


All about the research question

All about the research question

It’s not about learning a method, but learning how to answer different types of research questions.



Build models and interpret outputs in every session.



Includes lunch, morning coffee and pastries, mid-morning coffee and biscuits, and mid-afternoon coffee and cakes.



Get handouts and Mplus files to keep as work “companions” for your research.



An interactive course where you get to ask and answer questions throughout.



Get the full “Cambridge experience” in a university college.



Each day includes a quiz to help you grow your confidence.

Your research

Your research

Bring your own questions and ask me during the breaks.

Schedule (10 am – 5 pm)

Day 1

Day 1

Introduction to Path Analysis and Mplus

The power of SEM lies in the fact that it combines factor analysis and regression analysis. Thus SEM has two main components: the measurement paths and the structural paths. Path analysis refers to the structural paths and will be introduced on Day 1. We will also cover mediation analysis and the correct use of regression models, depending on features of the outcome variable. We will fit and discuss an assortment of models in Mplus.


  • Session 1: The SEM process
  • Session 2: Path analysis with mediated effects
  • Session 3: The different types of regression models
  • Session 4: Recap and Quiz


The programme is from 10am-5pm, split into 4 sessions of 1-1.5 hours each. Click on the other “bubbles” above to see the schedule for each day.

Day 2

Day 2

Factor analysis

The power of SEM lies in combining factor analysis with path analysis. Our instruments (e.g., questionnaires) most often rely on multiple indicators that attempt to tap into an unobserved underlying trait. With factor analysis we use information obtained from responses to items of the questionnaire to obtain insights into the underlying trait. As opposed to simple sum-scores, factor analysis is a more accurate representation of reality. Factor analysis comes in two flavours: exploratory and confirmatory.

Day 2 covers both EFA and CFA, alongside with the specification of a full SEM.


  • Session 1: Introduction to factor analysis
  • Session2: Exploratory and Confirmatory factor analysis
  • Session 3: Structural equation modelling
  • Session 4: Recap and Quiz
Day 3

Day 3

Multiple-group analysis

Research on differences between groups usually warrants two main research questions: ‘Are the average levels of a construct different between groups?’ and “Is the strength of the relationship between 2 (or more) constructs different between groups?”. But to answer both of these questions, the researcher must first ensure that the constructs measured function equivalently across groups. Can one truly conclude that 2 groups differ in a construct if it is revealed that the 2 groups under investigation interpreted the questionnaire differently?

Day 3 covers multiple group analysis and includes both information about measurement equivalence (i.e. invariance) and how to answer the main research questions of multiple-group studies.


  • Session 1: Multiple-group analysis and invariance testing
  • Session 2: Measurement invariance
  • Session 3: Structural invariance and Moderated mediation
  • Session 4: Recap and Quiz
Day 4

Day 4

SEM with longitudinal data

Structural equation modelling with longitudinal data can be a powerful tool in understanding behaviour over time. Although often disregarded, longitudinal invariance is essential for models where one wishes to compare mean levels over time and models depicting individual trajectories over time. Indeed, if the questionnaire was not interpreted in the same way at different time-points, how can one conclude that any observed differences in scores represented true differences?

In addition to providing an introduction to modelling using Mplus and explaining longitudinal invariance, Day 4 provides insights into path analysis with longitudinal data, auto-regressive (including cross-lagged) models and longitudinal mediation analysis.


  • Session 1: Auto-regressive models and Longitudinal mediation
  • Session 2: Longitudinal Confirmatory Factor Analysis
  • Session 3: Longitudinal CFA with measurement invariance constraints
  • Session 4: Recap and Quiz
Day 5

Day 5

Modelling individual trajectories over time

Modelling individual trajectories over time is one of the most interesting and revealing techniques that can be applied to longitudinal data. It can provide information about the general pattern of people’s behaviour and attitudes, as well as each person’s individual trajectory over time. This can then be incorporated into structural equation models to better understand the extent to which a variety of antecendents translate into steeper increases or decreases of a behaviour over time.

Day 5 covers latent growth curve models (linear, quadratic and piecewise) and further builds on these models to show how to answer research questions that pertain to the development and mutual relationship between 2 (or multiple) psychological constructs, as well as questions about predictors and outcomes of individual trajectories.


  • Session 1: Introduction to latent growth curve models
  • Session 2: The trajectory shape
  • Session 3: Dual growth models and Growth models with covariates
  • Session 4: Recap and Quiz
Day 6

Day 6

Group-based trajectories

Sometimes a single average trajectory doesn’t equally well describe your entire sample. In this case, it is likely that different sub-groups exist, each sub-group having its own trajectory of behaviour / attitudes over time. This is where group-based trajectory modelling comes in.

Day 6 covers the main tenets of identifying sub-groups of people with specific developmental trajectories over time and explains the difference between several major technique variations: growth mixture models, latent class growth analysis, latent profile analysis, longitudinal latent class analysis, etc. It also explains how you can use information on each person’s “profile” (i.e. trajectory group membership) to further build models that include covariates/predictors and outcomes.


  • Session 1: Introduction to group-based trajectory modelling
  • Session 2: Latent Class Growth Analysis and Growth Mixture Models
  • Session 3: Group-based trajectories with covariates; Further topics
  • Session 4: Recap and Quiz


Upcoming course: 2023 ON DEMAND

Courses in 2023 will be run on demand. So if you’d like a course, please “pre-register” below (free).

Course structure

  • 6 days: Monday – Sunday; Thursday is a “day off”, when you can explore and enjoy Cambridge.
  • The course fee is £960 (or £480 for one component) and it includes tuition, course materials and lunch, but does not include accommodation.
  • Bonus: after the course, you will be invited to take 1 iteration of the corresponding online course, thus covering the following 3 courses from the MplusWizard programme: Wizard’s Cat, Potion Master, Spell Caster.
  • To register:



My name is Gabriela Roman and I am a researcher based at the Institute of Criminology, University of Cambridge. I hold a PhD in developmental psychology (Cambridge University), an MPhil in criminological research (Cambridge University), and a BA in cognitive and social psychology (Jacobs University Bremen). My main research interest at the moment refers to self-concepts and self-regulation, with a particular focus on deconstructing interactions via virtual reality methodologies.

I developed an incipient version of this course in 2013, together with my friend Dr Arielle Bonneville-Roussy. This was hosted by the Psychometrics Centre within the Department of Psychology at the University of Cambridge. Teaching it and interacting with so many interested (and interesting!) participants has been a truly wonderful experience! In 2017, after Arielle left Cambridge, this course became a private (ad)venture, usually taking place 3 times each year (July, September and December).

I hope you will enjoy the course at least as much as I enjoy teaching it. Best wishes and I hope to see you soon!