Master-class September 2022: Mixed Effects Modelling: Online

This course is designed as an introduction to mixed effects modelling. These models involve data arising from longitudinal studies or studies where the data exhibits some form of hierarchy, and sometimes referred to as multilevel modelling.

 

Participants will be provided exercises and solutions in R.

 

 

This course is being held online via Zoom and run on Australian Eastern Standard Time (UTC +10)

(Melbourne, Sydney, Canberra, Brisbane time)

 

 

Dates: 
Friday, September 16, 2022 - Saturday, September 17, 2022
Early bird cutoff date: 
Wednesday, August 10, 2022
Course details:

This course is designed as an introduction to mixed effects modelling. These models involve data arising from longitudinal studies or studies where the data exhibits some form of hierarchy, and sometimes referred to as multilevel modelling.

 

 

This course will be offered online via Zoom And will run to the following timetable:

 

  • 9.30am - 11.00am: Instructional session
  • 11.00am - 11.30am: Break
  • 11.30am - 12.30pm: Instructional session
  • 12.30pm - 1.30pm : Lunch
  • 1.30pm - 3.00pm:  Instructional session
  • 3.00pm - 3.30pm: Break
  • 3.30pm - 4.30pm: Exercises & Discussion

 

Please note: Courses will run on Australian Eastern Standard Time (GMT +10)

 

 

 
Master Class - runs over 2 days
Course dates: Friday 16 September 2022 - Saturday 17 September 2022
Instructor: 

Dr Joanna Dipnall is a biostatistician with the School of Public Health and Preventative Medicine (SPHPM) at Monash University and Honorary Research Fellow with School of Medicine at Deakin University. She holds a B.Ec(Honours) from Monash University, and a PhD from the School of Medicine at Deakin University. She also lectures and tutors with the Department of Statistics, Data Science and Epidemiology at Swinburne University. Joanna has developed a novel Risk Index for Depression (RID) utilising SEM and machine learning techniques that brought together five key determinants of depression. She has been a teacher of Stata software for over 15 years, training across Australia and overseas and was a member of the Scientific Committee for the Oceania Stata Users Group Meeting in 2017.

Venue: 
Online
Week: 
Week 1
About this course: 

This course is designed as an introduction to mixed effects modelling. These models involve data arising from longitudinal studies or studies where the data exhibits some form of hierarchy, and sometimes referred to as multilevel modelling.

 

Mixed effects modelling is used when observations are not independent of each other (e.g., clustered data, repeated measures). This type of analysis is regularly used in such areas as educational research, when studying the performance of students within schools, and in medical research when investigating the outcomes over time following major trauma.

 

Mixed effects refer to the inclusion of both fixed effects (i.e., the variables that are constant across individuals), and random effects (i.e., account for variability among subjects around the relationships captured by the fixed effects).

 

This course will be discussing the linear mixed effects models, in which the outcome of interest is continuous. Discussion of some of the uses of mixed effects models in publications will be discussed at the end of the course.

 

Course syllabus: 

This course is broken up into the following sections:

Part I: Introduction to the Mixed Effects Model
Part II: Types of Hierarchical Data
Part III: Defining the Covariance Structures
Part IV: Inclusion of Random Effects
Part V: Reporting Mixed Effects Models
Part VI: Mixed Effects Models in Publications

 

Participants will be given time to do some exercises on their own to practise what they have learned.

 

Exercises and solutions will be provided in RMarkdown format.

Course format: 

This workshop will take place online using Zoom.

You will need your own computer with R and R Studio installed, and an internet connection.

A second screen/monitor is recommended.

Recommended Background: 

This course assumes that participants have:

(1) Sound familiarity with R, RMarkdown and RStudio.

(2) sufficient understanding of statistics to be able to comprehend the material covered in the course outline, such as a basic grounding in multiple regression (e.g., linear, logistic, Poisson)

(3) access to R and RStudio

(4) some experience in using Microsoft Word and Excel or their equivalent

(5) experience using a text editor such as Notepad.

 

Recommended Texts: 

Course notes will be supplied. Please include a shipping address when you enrol. Your notes will be express posted to this address.

 

No specific references are suggested but a number will be supplied with the notes handed out for the course.

Course fees
Early bird Member: 
$1,160
Early bird Non Member: 
$1,980
Early bird full time student Member: 
$720
Member: 
$1,480
Non Member: 
$2,280
Full time student Member: 
$1,280
Terms and Conditions: 

1. BOOKING - ACSPRI does not accept ‘expressions of interest’ for course places, i.e. all bookings, are considered firm, and a cancellation fee is charged if you cancel your booking after the early-bird date.

 

2. DISCOUNT RATE – The discounted rate for ACSPRI members is available to all staff and students of member organisations. To be eligible for this rate:

The course fee must be paid by either the member organisation or by you. Where fees are paid by a non-member organisation the non-member rate applies:and
You must either have a valid email address issued by the member organisation; or you must hold, or have a right to hold, a current staff or student identity card from the member organisation.

In addition, to be eligible for a full time student discount the participant must:

Hold, or have a right to hold, a current student identity card from the member organisation;
Be enrolled as a full-time student;
Make payment in full with your application, arrange electronic funds transfer (EFT), or contact ACSPRI to advise credit card details for payment, by the early-bird closing date;
Provide ACSPRI with contact details of your supervisor, so we can request them to confirm your eligibility for the full time student rate.

The early bird rate applies to all bookings paid in full by the early bird close date, otherwise you will be charged at the standard rate.

 

 

3. REFUNDS & CANCELLATIONS - Course fees are not refundable unless:

we cancel the course in which you have enrolled; or
you cancel your enrolment before the early-bird closing date.

A cancellation fee of $250 will be charged if you cancel within the period from the early-bird closing date of and one week prior to the commencement of the program. The full course fee will be charged if you cancel within 1 week of the beginning of your course.

 

4. PRE-REQUISITES - Course descriptions specify course pre-requisites. You must undertake to meet the pre-requisites of the course(s) in which you enrol. If in any doubt, you should contact ACSPRI prior to enrolling.

Venues: 

Delivery of this course is online - via Zoom.

 

Please ensure you have the following:

  • Reliable Internet connection with at least 5Gb per day of data available (i.e. a 5 day course will use about 25Gb of data just on the Zoom application)
  • A computer/laptop with the Zoom application installed (free)
  • A webcam (built in to most laptops)
  • A headset with a microphone (not required but ideal)
  • A second monitor/screen if possible

 

Please also check the course page for specific software requirements (if any).

 

Venue and Timetable: 

You will be attending from home, and each course may specify a slightly different timing schedule. Please expect around 4 "contact" hours per day, with the remainder of the usual working day for exercises, group work and self-directed activities.

All times specified are in Australian Eastern Time (Melbourne/Sydney/Canberra time)