Use of multiple regression methods in health sciences research. Development of linear, logistic, Poisson and Cox regression models for estimation and prediction including covariate adjustment, dummy variables, transformations and interactions.
This distance paper will introduce students to the main regression methods in health sciences research and is highly recommended for all students that want and/or need to analyse quantitative data. The paper builds on knowledge and skills learned in PUBH725 and also has a strong applied component. From a public health point of view, students will learn how to generate and interpret statistical models to adjust for confounders as well as identify the variables that have a statistical effect on the outcome of interest. Students will learn to use Stata, a leading statistical software package in Health Sciences Research. For this paper, students must have a computer with an Internet connection and be computer literate.
|Paper title||Applied Biostatistics 2 - Regression methods|
|Teaching period||1st Non standard period (10 July 2023 - 3 September 2023) (Distance learning)|
|Domestic Tuition Fees (NZD)||$1,509.38|
|International Tuition Fees||Tuition Fees for international students are elsewhere on this website.|
- HASC 413 or PUBH 725
- HASC 415, STAT 241, STAT 341
- Limited to
- MA, MAppSc, MClinPharm, MHealSc, MPH, MPharm, MPHC, MSc, DPH, PGDipAppSc, PGDipArts, PGDipHealSc, PGDipMLSc, PGDipPharm, PGDipSci, PGCertPH
- The prerequisite may be waived for students with an equivalent level of knowledge.
- Students who have completed an undergraduate degree in any discipline or recognised equivalent.
Department of Preventive and Social Medicine, Dunedin campus: firstname.lastname@example.org
- More information link
- View more information on postgraduate studies in Public Health
- Teaching staff
Associate Professor Gabrielle Davie
Professor Robin Turner
Dr Jimmy Zeng
- Paper Structure
- Simple linear regression
- Multiple linear regression
- Logistic regression
- Poisson regression
- Model diagnostics
- Participation and contribution: 10% of the marks for this paper will derive from your contribution to Zoom sessions and discussion forums. The marks will not be awarded for the correctness of your contributions, but for making an effort to engage with the question at hand.
- Assignment 1: This assignment, worth 40% of the mark for the paper.
- Assignment 2: This assignment, worth 50% of the mark for the paper.
- Teaching Arrangements
This Distance Learning paper is taught remotely.
- Compulsory webinar sessions: Tuesday afternoons, 4pm-6pm.
- Block Week (zoom webinars): Monday 17 th July, Tuesday 18th July, Wednesday 19 th July, 4pm-6pm.
E. Vittinghoff, D.V Glidden, S.C. Shiboski, C.E. McCulloch (2012). "Regression Methods in Biostatistics linear, logistic, survival, and repeated measures models, 2nd Edition."
- Graduate Attributes Emphasised
- Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking,
Information literacy, Research, Self-motivation.
View more information about Otago's graduate attributes.
- Learning Outcomes
Students who successfully complete the paper will be able to:
- Demonstrate an understanding of the application of regression methods to help answer scientific questions and the assumptions inherent in the models.
- Demonstrate skills in model selection, model fitting and model interpretation for estimation and prediction.
- Apply skills to develop a regression model and perform an analysis to help answer a scientific question.