BIOSTATS 6007EX - Categorical Data & Generalised Linear Models

External - Semester 2 - 2015

The aim of this course is to enable students to use generalised linear models (GLMs) and other methods to analyse categorical data with proper attention to the underlying assumptions. There is an emphasis on the practical interpretation and communication of results to colleagues and clients who may not be statisticians. The content includes: introduction to and revision of conventional methods of contingency tables especially in epidemiology; odds ratios and relative risks; chi-squared tests for independence; Mantel-Haenszel methods for stratified tables; and methods for paired data. The exponential family of distributions includes: generalised linear models (GLMs), and parameter estimation for GLMs; inference for GLMs-including the use of score, Wald and deviance statistics for confidence intervals and hypothesis tests, and residuals; binary variables and logistic regression models-including methods for assessing model adequacy; nominal and ordinal logistic regression for categorical response variables with more than two categories; and count data, Poisson regression and log-linear models.

• General Course Information
Course Details
Course Code BIOSTATS 6007EX Categorical Data & Generalised Linear Models Public Health Semester 2 Postgraduate Coursework External 3 Online N BIOSTATS 6000EX, BIOSTATS 6001EX, BIOSTATS 6003EX & BIOSTATS 6005EX BIOSTATS 6006EX Available to Grad Cert, Grad Dip, M Biostatistics students only The aim of this course is to enable students to use generalised linear models (GLMs) and other methods to analyse categorical data with proper attention to the underlying assumptions. There is an emphasis on the practical interpretation and communication of results to colleagues and clients who may not be statisticians. The content includes: introduction to and revision of conventional methods of contingency tables especially in epidemiology; odds ratios and relative risks; chi-squared tests for independence; Mantel-Haenszel methods for stratified tables; and methods for paired data. The exponential family of distributions includes: generalised linear models (GLMs), and parameter estimation for GLMs; inference for GLMs-including the use of score, Wald and deviance statistics for confidence intervals and hypothesis tests, and residuals; binary variables and logistic regression models-including methods for assessing model adequacy; nominal and ordinal logistic regression for categorical response variables with more than two categories; and count data, Poisson regression and log-linear models.
Course Staff

Course Coordinator: Dr Amy Salter

Course Coordinator : Dr Amy Salter
Phone: +61 8313 4619
Location: Level 8 Hughes Building
Course Timetable

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

• Learning Outcomes
Course Learning Outcomes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

University Graduate Attribute Course Learning Outcome(s)
Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. N/A
The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. N/A
An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. N/A
Skills of a high order in interpersonal understanding, teamwork and communication. N/A
A proficiency in the appropriate use of contemporary technologies. N/A
A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. N/A
A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. N/A
An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities. N/A
• Learning Resources
Online Learning
• Learning & Teaching Activities
Learning & Teaching Modes

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

Small Group Discovery Experience
• 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.

Submission

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
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 studentâ€™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.

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