Kaplan-Meier survival analysis
Kaplan-Meier survival analysis
Epidemiología
Epidemiología
Disease causality
Positive and negative predictive value
Sensitivity and specificity
Kappa coefficient
Incidence and prevalence
Odds ratio
Relative and absolute risk
Attributable risk (AR)
Study designs
Case-control study
Cohort study
Clinical trials
Randomized control trial
Selection bias
Information bias
Confounding
Interaction
Test precision and accuracy
Introduction to biostatistics
Types of data
Mean, median, and mode
Range, variance, and standard deviation
Probability
Prevention
Normal distribution and z-scores
Standard error of the mean (Central limit theorem)
Hypothesis testing: One-tailed and two-tailed tests
Type I and type II errors
Chi-squared test
Fisher's exact test
Paired t-test
Two-sample t-test
One-way ANOVA
Two-way ANOVA
Repeated measures ANOVA
Correlation
Methods of regression analysis
Linear regression
Logistic regression
Kaplan-Meier survival analysis
Mann-Whitney U test
Spearman's rank correlation coefficient
Sample size
Key Takeaways
Kaplan-Meier survival analysis is a statistical technique used to estimate the chance of survival (or failure) for a group of patients (or other objects) over time. It does this by partitioning the total time into intervals and computing the proportion of subjects who are still alive or still in the study at the end of each interval.