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PUBH726 Applied Biostatistics 2 - Regression methods

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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 identifying the variables that have a statistical effect on the outcome of interest. The regression topics covered include: analysis of variance, correlation, reliability studies, multiple linear regression and logistic regression. For this paper, students must have a computer with an Internet connection and be computer literate.

Students will learn to use a statistical software package commonly used in health sciences research (which software package is to be confirmed).

Paper title Applied Biostatistics 2 - Regression methods
Paper code PUBH726
Subject Public Health
EFTS 0.125
Points 15 points
Teaching period 1st Non standard period (11 July 2022 - 5 September 2022) (Distance learning)
Domestic Tuition Fees (NZD) $1,469.00
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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Prerequisite
HASC 413 or PUBH 725
Restriction
HASC 415, STAT 241, STAT 341
Limited to
MA, MAppSc, MClinPharm, MHealSc, MPH, MPharm, MPHC, MSc, DPH, PGDipAppSc, PGDipArts, PGDipHealSc, PGDipMLSc, PGDipPharm, PGDipSci, PGCertPH
Notes
(i) The prerequisite may be waived for students with an equivalent level of knowledge. (ii) MPHC students require approval from the Board of Studies in Primary Health Care to enrol for this paper. (iii) This paper runs for the second half of first semester. (iv) Please note that this paper will be offered in the first half of the second semester.
Eligibility
Students who have completed an undergraduate degree in any discipline or recognised equivalent.
Contact

Department of Preventive and Social Medicine, Dunedin campus: publichealth.dunedin@otago.ac.nz

Teaching staff

Paper Convenor: TBC

Paper Structure

Topics:

  1. Linear regression
  2. Logistic regression
  3. Poisson regression
  4. Model diagnostics

Assessment Structure:

  1. Participation and contribution - 10%
  2. Assessment 1 - 40%
  3. Assessment 2 - 50%
Teaching Arrangements
  1. Compulsory webinar sessions: Tuesday afternoons 4pm-6pm.
  2. Block Week (Zoom webinars): Monday 18th July, Tuesday 19th July, Wednesday 20th July, 4pm - 6pm
Textbooks

TBC

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
  • Describe and test the underlying assumptions of the model and carry out simple sensitivity analyses

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Timetable

1st Non standard period (11 July 2022 - 5 September 2022)

Location
Dunedin
Teaching method
This paper is taught through Distance Learning
Learning management system
Moodle