Event Date
This is a ‘LIVE COURSE’ – the instructors will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – Quebec (Canada) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
This course, based primarily on my 2016 book, teaches you how to use path analysis and structural equations modelling to test causal hypotheses using observational data that is typical of research in ecology and evolution. It is taught in half-day sessions so that you can practice individually after each half-day session. You will learn how to conduct these tests, why (and
when) they are justified, and how to interpret the results. The first few lectures will primarily present the theory but practical sessions will become more prominent later in the course. The
practical work will be based on R and RStudio. Students will receive R script, datasets, and a list of R packages to install. It is highly recommended that each student have a copy of my 2016 book for the course, but not essential.
Participants are encouraged to bring their own data, as there will be opportunities throughout the course to plan, analyze, and receive feedback on structural equation models.
Scientists generally, and ecologists specifically, who want to test hypotheses concerning cause-and-effect relationships involving several variables, especially involving observational data.
Delivered remotely
Time Zone – Quebec (Canada) local time
Availability – TBC
Duration – 9 days, 4 hours per day
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
This course involves a mixture of theory and practical work. Data and analytical approaches will be presented in a lecture format to explain key concepts. Statistical analyses will then be presented using R. All R script that the instructor uses during these sessions will be shared with participants, and R script will be presented and explained.
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
Day 1 – Classes from 08:30 – 12:30
Causal inference using experiments vs. observations (4h)
Day 2 – Classes from 08:30 – 12:30
Path analysis using piecewise structural equation modelling (1h30)
Practical work (2h)
Day 3 – Classes from 08:30 – 12:30
Path analysis using piecewiseSEM (2h30)
Practical work (1h)
Day 4 – Classes from 08:30 – 12:30
Equivalent models and AIC statistics (2h)
Practical work (1h30)
Day 5 – Classes from 08:30 – 12:30
Covariance-based path analysis (2h)
Covariance-based path analysis using lavaan (1h30)
Day 6 – Classes from 08:30 – 12:30
Latent variables and measurement models (3h)
Day 7 – Classes from 08:30 – 12:30
Practical using measurement models (1h)
The full structural equation model (2h30)
Day 8 – Classes from 08:30 – 12:30
Multigroup models (2h)
Practical: putting everything together (1h30)
Day 9 – Classes from 08:30 – 12:30
Practical and group presentations of results
Bill Shipley is an experienced researcher and teacher in plant ecology and statistical ecology. He has published four scientific monographs and over 170 peer-reviewed papers.