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Master of Science in Biostatistics
Biostatistics is a field of statistics concerned with designing, analysing and interpreting health research. The demand for biostatisticians far exceeds the supply, both in New Zealand and worldwide. The degree is taught jointly with the Department of Preventive and Social Medicine. This degree will be of benefit to:
- Students with an undergraduate degree in mathematics or statistics who wish to specialise in biostatistics
- Science students, such as those specialising in anatomy and structural biology
- Students with a health science degree who wish to develop their skills in analytic methods
The aims of the MSc in Biostatistics programme are to provide you with a solid underpinning of theoretical statistics, ensure that you are well-versed in modern biostatistical methods and that you have the ability to implement your knowledge of statistics effectively in a collaborative research setting.
Biostatisticians are needed in virtually all health sciences disciplines: epidemiology, public health, clinical research, basic medical sciences including genomics and physiology, behavioural research and health services research. Research areas which rely heavily on biostatisticians include clinical trials, prevention trials, community trials, observational studies of disease causation, surveys, bioinformatics, evaluation of diagnostic tests, pharmacovigilence and medical imaging studies.
This is normally a two-year degree.
Papers:
BIOS 501-504, 511
STAT 411, 412, 436, 440
HASC 411 or PUBH 701
From BIOS 505, 506, HASC 415, PUBH 722 (subject to approval), 400-level STAT, or other approved 400-level papers, to make a total of at least 240 points.
Research portfolio:
BIOS 501-504 are compulsory; BIOS 505 and 506 are optional. BIOS 501 and 502 must be taken in the first year of study.
Enquiries
Papers
BIOS 501-506 Research Portfolio details
(first and second semester) 24 points each
Under the supervision of a professional biostatistician, the student will develop skills and gain experience in collaborative research and consulting.
BIOS 511 Clinical Trials details
(first semester) 18 points
Fundamentals of the design and analysis of clinical trials, including randomization, sample size calculation, conduct of trials, the intention-to-treat principle, data safety monitoring boards, interim analyses and surrogate endpoints.
HASC 411 Research Design and Evaluation details
(first semester) 15 points
Principles of research design and the scientific and ethical evaluation of published research. Topics include study design, the interpretation of the results, and an introduction to the ethical appraisal of health research.
HASC 415 Regression Methods in Biostatistics details
(second semester) 15 points
The use of regression methods (e.g. linear, logistic, and Poisson regression for answering scientific questions in the health sciences. Topics include fitting/interpreting regression model and scientific issues in their application (e.g. outcome parameterization, model selection, missing data). Paper assignments give experience in data analysis using statistical software. Prerequisite: HASC413 or equivalent with approval.
PUBH 701 Epidemiology and Biostatistics details
(first semester) 30 points
Principles of epidemiology and biostatistics, including the basic principles and methods of different types of epidemiological studies; the critical appraisal of published research; and the application of epidemiology to public health and disease prevention.
STAT 411 Probability and Inference 3 details
(first semester) 18 points
An overview of the classical theory of statistical inference. Topics include stochastic convergence, laws of large numbers and the central limit theorem, classical estimation theory, Bayesian and likelihood inference.
STAT 412 Generalised Linear Models details
(second semester) 18 points
An introduction to the theory and applications of generalised linear models. Topics covered include Box-Cox transformations, loglinear models, models for ordered tables, generalised logit models, logistic models, censoring, accelerated failure time models, proportional hazards models, mixed models.
STAT 431 Bayesian Statistics details
(first semester) 18 points
Introduces the Bayesian approach to statistical inference. A theoretical basis is developed while computational issues are addressed using Monte Carlo Markov chain methods.
STAT 435 Data Analysis for Bioinformatics details
(second semester) 18 points
Topics include overview of genetics and molecular biology; genetic, genomic, and proteomic technologies; analysis of large data sets; application of standard and purpose built statistical methods; and incorporation of biological information into the statistical analysis process.
STAT 436 Survival Analysis details
(second semester) 18 points
Concepts of survival (time-to-event) analysis, including parametric, semi-parametric, and non-parametric methods. Topics include hazard functions, survival functions, types of censoring and truncation, Kaplan-Meier estimates, logrank tests, methods of estimation, and life tables.
STAT 440 Longitudinal and Mixed Model Analysis with Applications in Biostatistics details
(first semester) 18 points
Linear models for longitudinal data, covariance structures, random coefficients models, prediction, generalised linear mixed models, generalised estimating equations, nonlinear mixed effects models, design, power and sample size, missing data and simulation studies.
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