PUB HLTH 7104 - Biostatistics

North Terrace Campus - Semester 2 - 2015

This course is designed to suit students requiring a high degree of self-sufficiency in the collection, analysis and interpretation of data. The topics will include non-parametric statistical methods, linear models, logistic regression, Generalized Linear Models and Poisson regression, and survival analysis. A central feature of the course will be instruction in the use of statistical packages on computers, primarily Stata. Emphasis will be placed on data management and manipulation, practical application of statistical skills to real data sets and interpretation of results

  • General Course Information
    Course Details
    Course Code PUB HLTH 7104
    Course Biostatistics
    Coordinating Unit Public Health
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange N
    Prerequisites Credit standard in PUB HLTH 7074
    Restrictions Available to Grad Cert, Grad Dip, MPH & MHEP students only
    Course Description This course is designed to suit students requiring a high degree of self-sufficiency in the collection, analysis and interpretation of data. The topics will include non-parametric statistical methods, linear models, logistic regression, Generalized Linear Models and Poisson regression, and survival analysis. A central feature of the course will be instruction in the use of statistical packages on computers, primarily Stata. Emphasis will be placed on data management and manipulation, practical application of statistical skills to real data sets and interpretation of results
    Course Staff

    Course Coordinator: Associate Professor Lynne Giles

    Course Coordinator: Dr Lynne Giles
    Phone: +61 8313 0234
    Email: lynne.giles@adelaide.edu.au
    Location: Room 7-09, 178 North Terrace

    Learning and Teaching Team
    Phone: +61 8313 2128
    Email: postgrad_enq@adelaide.edu.au
    Location: Room 7-09, 178 North Terrace
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course, students will be able to:
    1 Manage and manipulate data efficiently and effectively;
    2 Apply a range of simple and complex statistical analysis techniques commonly used in Health Sciences appropriately;
    3 Demonstrate statistical reasoning skills correctly and contextually;
    4 Interpret results of statistical analyses in written summaries; and
    5 Use the statistical software package 'Stata' proficiently to conduct data manipulation and statistical 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)
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1, 2
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 2, 3, 4
    Skills of a high order in interpersonal understanding, teamwork and communication. 3, 4
    A proficiency in the appropriate use of contemporary technologies. 1, 5
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 3, 4
  • Learning Resources
    Required Resources
    The textbook for this course is: Armitage P, Berry G, Matthews JNS. Statistical Methods in Medical Research (4th edition). 2008; Wiley-Blackwell, London.

    An electronic version of the textbook may be accessed for free via the Barr Smith Library.

    Supplementary reading material will also be placed on MyUni.
    Recommended Resources
    Note that the Computing Suite (S118) in the Medical School South building is only open on weekdays from 9.00am until 7.00pm. There is no access on weekends.

    The University of Adelaide recently introduced Project ADAPT: http://www.adelaide.edu.au/its/adapt. ADAPT is any Device, any Place and Time. Students can access Stata 13 (and other software including R, SPSS and MATLAB) from their home computers and their portable devices (such as smartphones and tablets) via Project ADAPT. See the website above for more details.

    Students wishing to purchase their own copy of Stata 13 will need to do so through Survey Design and Analysis Services (the Australian distributor of Stata; see http://www.survey-design.com.au/gradplan.html). There are several options in their Grad Plan packages; price is determined by the length of licence, with prices ranging from »$100 to $200. Many students find the best option is the Advanced Grad Plan (which includes installation DVD with PDF of manuals + perpetual licence).

    Please check the Survey Design and Analysis Services website for exact prices at time of purchase, as cost may vary with the $US exchange rate.

    The Barr Smith Library is an important resource for any student of public health and in
    Orientation Week tours of the Library are arranged. The librarian with responsibility for public
    health is Maureen Bell.

    Useful texts and references will be discussed in class by the lecturers.
    A very important resource for students encountering any difficulties with mathematics or statistics at the University of Adelaide is the Maths Learning Centre based on Level 3 East of Hub Central, North Terrace Campus. For details go to http://www.adelaide.edu.au/mathslearning/.
    Online Learning
    Computers
    General information about University computer laboratories is available at
    http://www.adelaide.edu.au/its/student_support/labs/

    MyUni
    As an enrolled student, you will have access to the University’s on-line teaching facilities. This is an implementation of the Blackboard system called MyUni. MyUni is accessible from the University of Adelaide’s home-page: www.adelaide.edu.au . You will need your student login name and a password.

    If you do not have access, then either you are not enrolled or the administrators of MyUni do not know of your enrolment. Please call the Student Centre on 8313 5208 (Uni extension 35208) or the MyUni help desk on 8313 3335 (Uni extension 33335) for assistance with MyUni difficulties.

    Selected documentation for this course will be placed on MyUni including lecture overheads, lecture recordings, and data sets. Note also that Announcements about a course are often made on the relevant page of the MyUni site for the course. For example, notifications of a change in lecture venue, updates on availability of course material etc. will be made on the MyUni site.

    Email
    We assume that you have access to e-mail and that your address is the University of Adelaide student address that was assigned to you on enrolment. This is of the form:
    firstname.lastname@student.adelaide.edu.au
    A notice to a student by e-mail is considered to have been received and read by the student unless there is a transmission error and the postmaster bounces the message back to us. As discussed above, the Announcements page of the MyUni site for this course will also display relevant notices from time to time, so it is in your interest to check your student e-mail and to log on to MyUni regularly.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    There are a number of teaching and learning modes in this course. The course lectures provide basic factual information and concepts in biostatistics. Due to the limited timeframe, not everything will be covered in lectures. Lectures are intended to supplement material covered in the readings. Lectures will be supported by interactive practicals which are designed to develop software skills and clarify topics covered in the readings and lectures. These are problem solving sessions and students are required to prepare for these sessions. Assignments provide an opportunity to undertake exploratory and in-depth analysis of some key concepts introduced in the course, and demonstrate their understanding of biostatistical concepts.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    As a general rule in any university course, you will need to allow a minimum of three independent study hours for every hour undertaken in formal class work contact. This means that, for Biostatistics, you will need to set aside at least further nine hours per week for reading around topics, preparation for practicals, and submitting your 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. Students are expected to attend all lectures and practicals as completion of readings alone will almost certainly not provide sufficient material to enable a pass.
    Learning Activities Summary
    Week Topic Lecture/Practical
    Week 1 Managing data Lecture: Introduction, data sets, and statistical systems
    Practical: Getting started with Stata
    Week 2 Non-parametric statistical methods Lecture: Exploratory data analysis, Sign test, Wilcoxon rank-sum test
    Practical: Manipulating data and working with dates in Stata
    Week 3 Non-parametric statistical methods Lecture: Wilcoxon rank-sum test, Wilcoxon signed-rank test
    Practical: Assessing normality and non-parametric methods in Stata
    Week 4 Linear Models 1 Lecture: Simple linear regression and regression diagnostics
    Practical: Linear regression and regression diagnostics
    Week 5 Linear Models 2 Lecture: Multiple linear regression and model assumptions
    Practical: Fitting a multiple linear regression model
    Week 6 Linear Models 3 Lecture: Analysis of covariance and model assumptions
    Practical: Anova and ancova in Stata
    Week 7 Analysis of binary responses 1 Lecture: Measure of effect with binary data: Odds ratios, Mantel-Haenszel Odds ratios
    Practical: The Epitab suite
    Week 8 Analysis of binary responses 2 Lecture: Simple and multiple logistic regression
    Practical: Logistic regression models
    Week 9 Survival analysis 1 Lecture: Introduction to time to event data and life tables
    Practical: Life tables and survivorship functions
    Week 10 Survival analysis 2 Lecture: Introduction to Cox proportional hazards regression models
    Practical: Fitting a Cox model in Stata
    Week 11 Survival analysis 3 Lecture: Assessing the assumptions of Cox proportional hazards regression models
    Practical: Stratified Cox proportional hazards models
    Week 12 Generalized Linear Models Lecture: Introduction to common Generalized Linear Models
    Practical: Poisson regression and glm
    Specific Course Requirements
    N/A
    Small Group Discovery Experience
    N/A
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Assessment Type Weighting Learning Outcome(s) being addressed
    Multiple choice quiz: Interpreting Stata output Summative 5% 2, 3, 4
    Data management and interpretation exercise Summative 35% 1-5
    Statistical analysis project Summative 50% 1-5
    Engagement in lectures and practicals Formative and summative 10% 3, 4
    Assessment Related Requirements
    To pass this course, you must achieve 50% overall, and a pass (50% or more) in the Statistical Analysis Project.
    Assessment Detail
    All assessment tasks will be distributed via hardcopy in lectures. All assessment tasks will be assessed according to the University's M10 mark scheme.
    Submission
    Assignments can only be submitted in hardcopy form either to someone at Reception or through the slot in the locked box at the Discipline of Public Health, Level 7, 178 North Terrace. The appropriate cover sheet must be attached to each assignment. These coversheets are available through MyUni.
    Each student submitting an assignment must also sign and date the designated class list (for this course and this assignment) which will be available at Reception. You will be advised if you are also required to submit an electronic version of your assignment.

    Assignments must be submitted by 4.00pm on the due date. The locked box will be emptied every day at this time.

    Multiple pages should be stapled at the top left hand corner, irrespective of whether a protective plastic sleeve is used. Each page 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. It is prudent to keep a photocopy of your assignment.

    An assignment may not be submitted by e-mail or by fax and should not be given to lecturers or tutors in an ad hoc fashion at the time of lectures or tutorials. Marked assignments can be collected from the Discipline of Public Health.

    Extensions 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. Only the course coordinator(s), or a person authorised by him or her, may grant extensions.
    Documentary supporting evidence such as a medical certificate or a police report (in the case of lost computers, car & household theft etc.) will usually be required when requesting an extension.

    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 finalised “in time for graduation” for post-graduate courses or “in time to meet usual University deadlines”.

    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, marks will then be deducted from the mark awarded, at the rate of 5 percentage points of the total possible per day. For example, if an assignment which is 2 days late is awarded 65% on its merits, the mark will then be reduced by 10 (5 marks per day for 2 days) to 55%. If that same assignment is 4 days late its mark will be reduced by 20 (5 marks per day for 4 days) to 45% etc.

    The Discipline reserves the right to refuse to accept an assignment that is more than 7 days late.
    Course Grading

    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.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.