Structural Equation Modelling

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Please note that, at this stage, this event is fully booked. Nevertheless, you are most welcome to register for this event, and accordingly, we will place you in a waiting list. Should any of the registered participants cancel his/her registration (which is quite common), we will notify you and ask you whether you would still like to participate in this event. If we do not contact you again with respect to this event, you may assume that no vacancies have arisen.

Structural Equation Modelling

9 - 13 January 2023 

Scope

sem.jpgWhile much of statistics focusses on associations between variables and making predictions, the aim of structural equation modelling is to test multivariate causal hypotheses and to estimate causal relationships between variables. In spite of the common belief that any causal statement requires randomized experiments, there is an increasing body of theory, methodology and software that enables scientists to draw certain types of causal conclusions from observational data. This has important advantages, especially in cases where randomized experiments are not feasible. Notably, causal models allow the quantification of intervention effects, which is the response of the system given a certain value of one your variables (e.g. rainfall). This new course will explain the key concepts underlying causal inference, the required assumptions, and how the interpretation of results differs from the case of randomized experiments. To ensure that you learn from the best, we managed to get Prof. Bill Shipley from the Université de Sherbrooke in Canada to come over to Wageningen to actually give this course. Prof. Shipley is the author of "Cause and correlation in biology: A user’s guide to path analysis, structural equations, and causal inference with R", which by many is seen as the guide for working with Path Analysis and Structural Equation Models. The focus will be on classical structural equation models with latent variables and generalisations of path analysis via d-separation and directed acyclic graphs using the R program. Throughout the course we will discuss applications in ecology, evolution, and other areas of biology. Depending on the background and interests of the participants we may put a stronger emphasis on some of these applications. Participants are therefore encouraged to bring their own data.

Programme
  • Day 1: Introduction and background of structural equation models (SEM): causation versus correlation, causal inference versus ‘classical’ statistics. d-separation and piecewise path analysis.
  • Day 2: Path analysis via classical SEM and maximum likelihood. Testing and selecting your model: goodness of fit tests, model comparison, the lavaan package in R.
  • Day 3: Adding latent (unmeasured) variables to your model; concept of latent variables, estimating SEMs with latent variables.
  • Day 4: Robust methods, alternative fit indices, multigroup models.
  • Day 5: Exploratory methods.
General information
Target Group The course is aimed at PhD candidates and other academics
Group Size Min. 15 / Max. 30 participants
Course duration 5 days
Language of instruction English
Frequency of recurrence Once every two or three years
Number of credits 1.5 ECTS
Lecturers Prof. Bill Shipley (Université de Sherbrooke, Canada) and Dr. Bob Douma (Centre for Crop Systems Analysis, Wageningen University & Research)
Recommended Literature Cause and correlation in biology : A user’s guide to path analysis, structural equations, and causal inference in R. Cambridge University Press. This book is included in the course fee (as a digital PDF file) and will thus be offered to you about 2 weeks prior to the start of the course.
Prior knowledge Although the emphasis will be on the concepts rather than mathematical properties, some basic knowledge of probability and statistics will be required to understand those concepts. In particular, we will assume familiarity with random variables, joint distributions of random variables, conditional distributions and multiple regression. Basic knowledge of R is recommended (e.g. installing packages, reading data-files, linear regression).
Location Wageningen University Campus
Options for accommodation Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For non-WUR PE&RC members 50% of the accommodation costs can be reimbursed with a maximum of €30,- per night. For more information contact Jacqueline Verhoef. For information on B&B's and hotels in Wageningen please visit proefwageningen.nl. Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Finally, there are a number of groups on Facebook where students announce subrent possibilities and things like that. Examples include: Wageningen Room Subrent, Wageningen Room Sublets, and Wageningen Student Plaza. Wageningen has a range of restaurants, but there are also options to have dinner on the University Campus.
Fees 1
  EARLY-BIRD FEE 2 REGULAR FEE 2
PE&RC / WIMEK / WASS / EPS / VLAG / WIAS / RSEE  PhD candidates with an approved TSP € 190,- € 240,-
PE&RC postdocs and staff  € 380,- € 430,-
All other academic participants € 420,- € 470,-
Non academic participants € 610,- € 660,-

1 The course fee includes all course materials (including the PDF versions of the book about Structural Equation Modelling).
2 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 14 November 2022

Note:

  • If you need an invoice to complete your payment, please send an email to office.pe@wur.nl, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
PE&RC Cancellation Conditions
  • Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
  • Up to 2 (two) weeks prior to the start of the course, a fee of € 190,- will be charged.
  • In case of cancellation within two weeks prior to the start of the course, a fee of € 420,- will be charged.
  • If you do not show at all, a fee of € 610,- will nevertheless be charged.

Note: If you would like to cancel your registration, ALWAYS inform us and do not assume that by NOT paying the participation fee, your registration is automatically cancelled, because it isn't (and do note that you will be kept to the cancellation conditions).

More information

Dr. Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485426
Email: claudius.vandevijver@wur.nl

Registration

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