PUB HLTH 3009 - Experimental Research Design and Analysis
North Terrace Campus - Semester 1 - 2019
General Course Information
Course Code PUB HLTH 3009 Course Experimental Research Design and Analysis Coordinating Unit Public Health Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Prerequisites PUB HLTH 2007 or approval by course coordinator Course Description Principles in the design of experimental research studies and practical skills in the statistical analysis of results will be developed in this course. Topics will include construction of research hypotheses, principles of statistical inference, confidence interval estimation, and differences in statistical approaches in the clinical trials setting. Students will undertake analyses of study data where outcomes are continuous or binary, and understand the role of unvariable and adjusted analyses. Students will carry out sample size calculations appropriate to different study designs. Interpretation and critical appraisal of contemporary publications of experimental studies using the CONSORT guidelines will be built upon throughout this course.
Course Coordinator: Dr Amy SalterCourse Coordinator: Dr Amy Salter
Phone: +61 8313 4619
Location: Level 9, Adelaide Health & Medical Sciences Building, North Terrace Adelaide
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes1 Apply common clinical trial designs appropriately in addressing research questions
2 Distinguish between primary and secondary outcome variables and demonstrate knowledge of different types of variables
3 Apply a range of simple and complex statistical analysis techniques commonly used in clinical trials, including intention to treat, per protocol and as treated approaches
4 Demonstrate statistical reasoning skills correctly with unadjusted and adjusted parallel group analyses
5 Interpret published literature against CONSORT statement
6 Use ‘Stata’ statistical software proficiently to conduct unadjusted and adjusted parallel group analyses
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1 - 6 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
3 - 6 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
5 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1 - 6
Required ResourcesThe textbooks for this course are:
1. Matthews N.S. Introduction to Randomized Controlled Clinical Trials (2nd edition). 2006; Chapman and Hall.
2. Bland M. An Introduction to Medical Statistics (4th edition). 2015; Oxford University Press.
Please note: Both texts are available for short-term loan via the Barr Smith Library, although it is advisable that you purchase a copy of Matthews (2006).
Bland (2015) is the required textbook for the pre-requisite course PUB HLTH 2007. If you do not already own a copy of this text, selected readings will be made available electronically.
Recommended ResourcesA list of recommended resources that will supplement the lectures, text book and readings, will be provided on MyUni ahead of each teaching week.
General information about University computer laboratories is available at
As an enrolled student, you will have access to the University’s online teaching facility, known as MyUni. MyUni is accessible from the University of Adelaide’s home-page: www.adelaide.edu.au
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Course materials will be placed on MyUni including lecture slides, lecture recordings, tutorials, and practicals. Note also that Announcements about the course will be made on MyUni.
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Learning & Teaching Activities
Learning & Teaching ModesLectures are intended to introduce concepts and illustrate their use.
Tutorials and Computer Practicals provide an interactive forum to apply concepts from lectures and clarify understanding. In the series of computer practicals a statistical package (Stata) will be used to analyse data.
Assignments provide an opportunity for independent application and exploration of key concepts, for wider reading and for synthesis of concepts and literature.
The exam provides an opportunity for students to demonstrate what they have learnt, drawing together concepts and showing that they understand key concepts in the design and analysis of experimental studies.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.Enrolment in Design and Analysis of Experimental Studies III begins with the assumption that students are active participants in the learning process, rather than passive recipients of information. We assume that you are willing and able to prepare fully for classes, to participate in discussions and to carry your share of the workload.
As a general rule, in any university course you will need to allow a minimum of 3 independent study hours for every hour undertaken in formal class work contact. This means that you will have to set aside at least a further 9 hours per week for reading around topics, preparation for class activities, and work on assignments.
You are urged to bear this in mind when planning your university timetable, particularly if you are also engaged in paid employment. In our experience, students may not be able to demonstrate their full capacity if they are working full-time and studying full-time.
Learning Activities SummaryA detailed timetable of classes and assessment tasks will be available in the course Handbook, and on MyUni. The topics covered in lectures, tutorials and practicals include:
- History of clinical trials
- Phase I-IV trials
- Governance and Regulatory framework
- Features of a Randomised Controlled Trial
- The CONSORT statement
- Constructing Research Hypotheses
- Principles of Statistical Inference
- Confidence interval estimation
- Sample size estimation
- Statistical analyses of continuous and binary outcomes
- Univariable and adjusted analyses
- Critical appraisal of published study results using the CONSORT guidelines
Specific Course RequirementsN/A
Small Group Discovery ExperienceN/A
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Task Type Weighting Learning Outcome
Tutorial & Practical preparation Summative 10% 1 - 6
Assignment 1: Importance of Summative 5% 1, 2
Randomised Controlled Trials
Assignment 2: Addressing the Summative 15% 1 - 3, 5
Assignment 3: Analysis and Summative 20% 3, 4, 6
reporting of RCTs
Exam Summative 50% 1 - 6
Assessment Related RequirementsStatistical methods are necessarily somewhat technical in parts and a basic proficiency with numerical methods and a familiarity with statistical concepts introduced in PUB HLTH 2007 is assumed. As with PUB HLTH 2007, the level is somewhere around that of Year 10 of secondary school. That is, a familiarity with simple algebraic and graphical techniques and simple maths symbols is required. No calculus or trigonometry is needed. If you can decipher these types of symbols:
± x^(2) √x π log(x) ∑ xi
and you know what a fraction, negative number and an X-Y plane are, and can solve simple algebraic equations, then you are prepared. If not, acquaintance with a basic maths book is in order. Like most things worth learning, the kernel of statistics is about ideas rather than techniques. Knowing a little of the “language” will help you to appreciate the ideas. Please do not leave this preparation until the beginning of the course; some will find that this is too late.
To pass this course, a student must submit all three assignments and score at least 50% overall (for combined component assessments).
Assessment DetailTutorial and practical preparation and participation (10%)
Unless otherwise indicated, each week you will be required to prepare answers to tutorial and practical questions and submit them prior to class. Further details can be found in the Course Handbook and on MyUni.
Assignment 1 (5%)
Understanding the importance of Randomised Controlled Trials
Assignment 2 (15%)
Addressing the CONSORT statement
Assignment 3 (20%)
Analysis and reporting in Randomised Controlled Trials
All assessment tasks will be made available on MyUni at least 2 weeks prior to the date of submission. All assessment tasks will be assessed according to the University’s M10 mark scheme.
SubmissionAssignments should be submitted online through MyUni. Assignments must be submitted by 11:59pm on the due date.
A mixture of typeset and handwritten assignments are acceptable (especially for mathematical work) provided that they are neat and legible. All assignments must be scanned and submitted electronically (as word or pdf documents).
Each page of an assignment should be numbered and the total number of pages should appear on each page (e.g. “page 2 of 4” or “2/4”). The first page should bear the student’s name and student number; each subsequent page should bear, at least, the student’s initials.
Marked assignments will be available through the Grade Centre in MyUni.
All extensions for assignments must be requested, at the latest, by the last working day before the due date of submission. Extensions will generally be granted only on medical or genuine compassionate grounds. Supporting documentation must be provided at the time a student requests an extension. Without documentation, extensions will not be granted. Late requests for extension will neither be accepted nor acknowledged.
Only the Course Co-ordinator may grant extensions.
Supporting documentation will be required when requesting an extension. Examples of documents that are acceptable include: a medical certificate that specifies dates of incapacity, a police report (in the case of lost computers, car & household theft etc.), a letter from a Student Counsellor, Education and Welfare Officer (EWO) or Disability Liaison Officer that provides an assessment of compassionate circumstances, or a letter from an independent external counsellor or appropriate professional able to verify the student’s situation. The length of any extension granted will take into account the period and severity of any incapacity or impact on the student. Extensions of more than 10 days will not be granted except in exceptional circumstances.
Marks will be deducted when assignments for which no extension has been granted are handed in late.
All assignments, including those handed in late, will be assessed on their merits. In the case of late assignments where no extension has been granted, 5 percentage points of the total marks possible per day will be deducted. If an assignment that is 2 days late is awarded 65% on its merits, the mark will then be reduced by 10% (5% per day for 2 days) to 55%. If that same assignment is 4 days late, the mark will be reduced by 20% (5% per day for 4 days) to 45%, and so on.
Assignments submitted after the due date may not be graded in time to be returned on the listed return dates. The School of Public Health reserves the right to refuse to accept an assignment that is more than 7 days late.
Students submitting examinable written work who request (and receive) an extension that takes them beyond the examination period are advised that there is no guarantee that their grades will be processed in time to meet usual University deadlines.
If a student is dissatisfied with an assessment grade they should follow the Student Grievance Resolution Process <https://www.adelaide.edu.au/student/grievance/process/>. Students who are not satisfied with a particular assessment result should raise their concerns with Course Co-ordinator(s) in the first instance. This must be done within 10 business days of the date of notification of the result. Resubmission of any assignment is subject to the agreement of the Course Co-ordinator(s) and will only be permitted for the most compelling of reasons.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
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SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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