Logistic regression analysis
OVERVIEW
Logistic regression analysis is used to predict a dependent binary outcome (yes/no, dead/alive) based on one or more predictor variables
- most commonly used to perform multivariate analysis (controlling for various factors)
- ICU mortality predictions are based on logistic regression analysis
VARIABLES
- Logistic regression can be binomial (yes/no) or multinomial (good/neutral/bad)
- the dependent variably is categorical (yes/no, dead/alive)
- the predictor variables are usually continuous (but can be categorical)
ESTIMATION AND GOODNESS OF FIT
- The regression coefficients are usually estimated using maximum likelihood estimation (there are other methods)
- Goodness of fit can be determined by multiple methods (e.g. Chi-square goodness of fit tests and deviance, Hosmer-Lemeshow tests, Classification table, ROC curves, Logistic regression R2 and Model validation via an outside data set or by splitting a data set)
REGRESSION COEFFICIENTS
- regression coefficients allow the contribution of different predictor variables to be analysed
- likelihood ratio test and the Wald statistic can be used
Critical Care
Compendium
Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also a Clinical Adjunct Associate Professor at Monash University. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.
After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.
He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE. He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of litfl.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.
His one great achievement is being the father of three amazing children.
On Twitter, he is @precordialthump.
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