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    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 PUBH 725 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.

    About this paper

    Paper title Applied Biostatistics 2 - Regression methods
    Subject Public Health
    EFTS 0.125
    Points 15 points
    Teaching period 1st Non standard period (8 July 2024 - 30 August 2024) (Distance learning)
    Domestic Tuition Fees ( NZD ) $1,551.63
    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:

    Teaching staff

    Paper Convener: Dr Brett Maclennan

    Paper Structure
    1. Simple linear regression
    2. Multiple linear regression
    3. Logistic regression
    4. Poisson regression
    5. Model diagnostics

    Assessment Structure

    1. 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.
    2. Assignment 1: This assignment, worth 40% of the mark for the paper.
    3. Assignment 2: This assignment, worth 50% of the mark for the paper.
    Teaching Arrangements

    This Distance Learning paper is taught remotely.

    1. Compulsory webinar sessions: Tuesday afternoons 4pm-6pm.
    2. Block Week (Zoom webinars): Monday 15th July, Tuesday 16th July, Wednesday 17th 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.


    1st Non standard period (8 July 2024 - 30 August 2024)

    Teaching method
    This paper is taught through Distance Learning
    Learning management system
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