Statistics and interpretation of evidence

By Alex Yartsev - 14/07/2015

Offered below is an organised list of summaries on the topic of statistics and EBM from the Critical Care Compendium, courtesy of LITFL. Given the mixture of topics, the ideal audience for this material is the final stage exam candidate pursuing dual CICM and ACEM fellowship qualifications.

Statistics and Evidence-Based Medicine in the Critical Care Compendium
Evidence-based medicine Evidence based medicine Levels and grades of evidence Types of research studies Animal and laboratory studies, knowledge translation Case reports and case series Meta-analysis and systematic review Analysis of data Understanding Diagnostic Tests, decision making, diagnosis, likelihood ratio, sensitivity, specificity, positive, negative, predictive value Validity of Clinical Research, trial How to analyse a clinical trial Subgroup analysis Propensity Score Analysis Statistical Significance and Clinical Significance Clinical Trials Randomised control trials, RCT, RCTs Phases of Clinical Research, Trials Early Stopping of Trials Clinical trial design How to conduct a clinical trial Power and Sample Size Calculation Intention to treat analysis Blinding and Allocation Concealment Randomisation Outcome measures ICU Outcomes Intensive Care Outcomes Surrogate outcomes Statistical methods Linear regression and Correlation Logistic regression analysis Measures of central tendency Measures of variability Chi square test Confidence intervals Data distributions Fishers exact test Hazard Ratio, Median Ratio and Kaplan-Meier Curves Odds ratio Incidence and prevalence Receiver Operating Characteristics (ROC) Curve, diagnostic test Risk and Numbers needed to treat, NNT Data types and tests Qualitative data types and tests Quantitative data types and tests Errors in medical research Precautionary Principle and the Kehoe Principle Dogma and Pseudoaxioms Medical Reversal Publication Practices Distort Science, economics Error in Research Bias in Research, clinical trials Interpretative biases Confounding, Confounders Practice Misalignment

[Submit a comment or correction]

Statistics and interpretation of evidence

Evidence-based medicine

Analysis of data

Clinical Trials

Clinical trial design

Outcome measures

Statistical methods

Data types and tests

Errors in medical research