sta5arm analysis of repeated measures
ANALYSIS OF REPEATED MEASURES
STA5ARM
2017
Credit points: 15
Subject outline
Repeated measures data is used commonly in many disciplines including health, psychology, economics and biology. This subject provides students with the knowledge of how to perform the appropriate statistical analysis in a repeated measures data environment by introducing models such as the Repeated Measures ANOVA, Marginal models, Linear mixed models and Correlated random effect models. Students will learn how to examine research questions by applying these models using the R statistical package.
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorDavid Farchione
Available to Study Abroad StudentsYes
Subject year levelYear Level 5 - Masters
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites Must be enrolled in SMDS Master of Data Science course and have completed STA4SS or equivalent. All other students require approval of the Head of Department of Mathematics and Statistics.
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Special conditionsN/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Analysis of Repeated Measures | Prescribed | Farchione 2017 | La Trobe University |
Graduate capabilities & intended learning outcomes
01. Use specialised computer software to critically analyse, reflect on and summarise complex information, problems and concepts for repeated measures data.
- Activities:
- Online Lectures: This consists of readings from the prescribed textbook; and online video clips that (i) explain the readings and (ii) cover practical examples using the R computer package. Computer Labs: Students in this class work through practical examples using the R computer package. Online Discussion Forum: Topics covered in Online Lectures and Computer Labs are discussed by students and teachers via the asynchronous online discussion forum.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
02. Demonstrate an understanding of complex repeated measures regression models by expressing a research question in the form of a regression model.
- Activities:
- Online Lectures: This consists of readings from the prescribed textbook; and online video clips that (i) explain the readings and (ii) cover practical examples using the R computer package. Computer Labs: Students in this class work through practical examples using the R computer package. Online Discussion Forum: Topics covered in Online Lectures and Computer Labs are discussed by students and teachers via the asynchronous online discussion forum.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
03. Use advanced written communication skills to disseminate findings from analyses of repeated measures data at a level commensurate with what is appropriate in the scientific literature for a range of disciplines.
- Activities:
- Online Lectures: This consists of readings from the prescribed textbook; and online video clips that (i) explain the readings and (ii) cover practical examples using the R computer package. Computer Labs: Students in this class work through practical examples using the R computer package. Online Discussion Forum: Topics covered in Online Lectures and Computer Labs are discussed by students and teachers via the asynchronous online discussion forum.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
04. Use advanced verbal and written communication skills to critique published analyses of repeated measures data and to justify findings that result from applying a variety of methods.
- Activities:
- Online Lectures: This consists of readings from the prescribed textbook; and online video clips that (i) explain the readings and (ii) cover practical examples using the R computer package. Computer Labs: Students in this class work through practical examples using the R computer package. Online Discussion Forum: Topics covered in Online Lectures and Computer Labs are discussed by students and teachers via the asynchronous online discussion forum.
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Literacies and Communication Skills(Writing,Speaking,Quantitative Literacy)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
Subject options
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Melbourne, 2017, Semester 1, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorDavid Farchione
Class requirements
Unscheduled Online ClassWeek: 10 - 22
One 2.0 hours unscheduled online class per week on any day including weekend during the day from week 10 to week 22 and delivered via online.
Computer LaboratoryWeek: 11 - 22
One 2.0 hours computer laboratory every two weeks on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
"Even teaching weeks."
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Online Quizzes (Equivalent to 500 words) | Students can attempt each quiz a maximum of three times and the best mark for that quiz is taken. Randomly assigned questions for each quiz instance. | 10 | 02 |
| Two written assignments, submitted online (Equivalent to 1000 words in total) | 20 | 01, 02, 03 | |
| Written project (Equivalent to 1000 words) | Students must choose a recently published paper that uses repeated measures data for appraisal/critique. | 20 | 01, 02, 03, 04 |
| 2.5 hour Final Exam (Equivalent to 2500 words) | 50 | 01, 02, 03, 04 |