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Introduction To Multiple Linear And Multiple Logistic Regression In Health Research Using Sas And R

  • 8 Oct 2020
  • 9:00 AM
  • 12 Oct 2020
  • 5:30 PM

Introduction To Multiple Linear And Multiple Logistic Regression In Health Research Using Sas And R 

This workshop will provide learners with the foundational knowledge and skills to perform multiple linear and multiple logistic regressions in the context of public health and medical research. 

This is a hands-on online learning workshop which will run across 3 days. Learners can register for one or both topics across the 3 days: 

Topic 1

-        Multiple Linear Regression Part 1 (8th October 2020, 9am – 5:30pm)

-        Multiple Linear Regression Part 2 (9th October 2020, 9am – 2:30pm)

Topic 2

-        Multiple Logistic Regression (12th October 2020, 9am – 5:30pm)

Learning Materials: Learners will be provided with an opensource online tutorial that will need to be completed prior to attending the workshop

Software information: SAS is a statistical software system widely used in a range of industries including the pharmaceutical, healthcare, marketing research and financial industry. In contrast, R language is an open-source programming language and software-package maintained by the R core-development team. Also, the R language is used for performing statistical operations and is a command-line driven program. Nowadays, SAS and R are considered as the most popular analytics tools in the world. Further, it is estimated that R users range from 250000 to over 2 million. 

Prerequisite Knowledge of basic statistics: Descriptive statistics, univariate statistical tests, correlation and simple linear regression 

Cost ($275 for students in each topic with total $550 for both)

Topic 1 - $375

Topic 2 - $375

Topic 1 and 2 - $750

About the Lecturer

Dr Haider Mannan is a biostatistician at Translational Health Research Institute and the School of Medicine, Western Sydney University. His biostatistical expertise is wide including regression models for clustered and longitudinal data (e.g. multilevel mixed effects, GEE models), continuous, binary (e.g. logistic regression), survival (e.g. Cox regression, Weibull regression), categorical and ordinal outcomes, nonparametric methods, analysis of small studies, state transition models (e.g. Markov simulation/model, latent Markov model), to note a few, all in the context of epidemiological/health studies. He has published several software in peer reviewed journals for disease risk modelling using SAS macros. He has published two monographs,55 peer reviewed articles in epidemiology/biostatistics with 25 as first authored and 24 in category 'A' journals including International Journal of Obesity, Obesity, Appetite, International Journal of Eating Disorders, American Journal of Epidemiology, BMJ Open, Journal of Affective Disorders, Preventive Medicine, European Journal of Preventive Cardiology, Annals of Epidemiology, European Journal of Nutrition, Accident Analysis and Prevention, Statistical Methods in Medical Research etc. He teaches and coordinates a biostatistics unit for Master of Epidemiology, MPH and MHSc courses during spring semester. This unit focuses on application of commonly used multivariate statistical methods in public health. He has excelled in teaching this unit having obtained a perfect score of 5 in spring 2019. He also teaches introductory biostatistics to MBBS and MD students, conducts internal workshops on multilevel and multivariate regression models as well as online research workshops.

He earned a Ph.D. in biostatistics and epidemiology from University of Western Australia with distinction in 2008, and then worked for 6 years at the Monash University Department of Epidemiology and Preventive Medicine and James Cook University as Senior Research Fellow. 

Deadline for Registration: 6 October 2020


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