Statistics for Trauma Research
Part I: The Bare Essentials: Wax on, wax off
I.
II.
III.
IV.
V.
VI.
What is statistics and why do we need it?
a. General definition
b. Goals of statistics in a clinical setting
c. Variability
d. Issues/limitations
e. Descriptive vs. inferential (analytic) statistics
Variables
a. Dependent vs. independent
b. Variable levels:
i. Discrete: nominal, ordinal
ii. Continuous: interval, ratio
Describing data with numbers
a. Central tendency: Mean vs. Median
b. Dispersion
i. Range
ii. Interquartile range
iii. Variance and standard deviation
Summarizing data visually
a. Frequency tables
b. Charts, graphs
c. Box plots
Quantifying extent of disease
a. Prevalence
b. Incidence
i. Cumulative incidence
ii. Incidence rate
Comparing extent of disease
a. Risk difference (aka excess risk, aka attributable risk)
i. Attributable fraction
b. Relative risk
c. Odds ratio
Statistics for Trauma Research
Part II: Basics of Probability, and types of distributions
I.
II.
III.
IV.
V.
VI.
VII.
VIII.
Basic probability (“likelihood,” “risk”)
Conditional probability
Sensitivity vs. Specificity
Predictive value: positive and negative
Independence
Binomial distribution
Normal distribution
Central Limit Theorem
Part III: Statistical Inference
I.
II.
III.
IV.
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VI.
VII.
VIII.
IX.
X.
XI.
XII.
Decision matrix
P-values
Type I, Type II, alpha, Beta
Continuous outcome, 1 sample
Continuous outcome, 2 samples
Categorical outcome, 1 sample
Categorical outcome, 2 samples
Continuous outcome, 3+ samples: ANOVA
Categorical outcome, 3+ samples
Statistical vs. clinical significance
Confidence intervals
P-values vs. confidence intervals
Part IV: Nonparametric Tests
I.
II.
III.
What are they, and why do we need them?
Categorical outcomes
Part V: Multivariable Statistics
I.
II.
III.
Simple Regression
Multiple linear regression
Multiple logistic regression
Part VI: Sample Size and Power
Part VII: Survival Analysis