Tables for epidemiologists
2 × 2 and 2 × 2 stratified tables for longitudinal, cohort study, case–control, and matched case–control data
Odds ratio, incidence ratio, risk ratio, risk difference, and attributable fraction
Confidence intervals for the above
Chi-squared, Fisher’s exact, and Mantel–Haenszel tests
Tests for homogeneity
Choice of weights for stratified tables: Mantel–Haenszel, standardized, or user specified
Exact McNemar test for matched case–control data
Tabulated odds and odds ratios
Score test for linear trend
Watch Odds ratios for case–control data in Stata.
Watch Stratified analysis of case–control data in Stata.
Watch immediate commands in Stata with summary data tutorials
Power and sample size
Stratified 2×2 tables (Cochran–Mantel–Haenszel test)
1:M matched case-control studies
Trend in J×2 tables (Cochran–Armitage test)
Standardization of rates
Direct standardization
Indirect standardization
Generalized linear models for the binomial family
Individual-level or grouped data
Odds ratios, risk ratios, health ratios, and risk differences
Bayesian estimation
Table symmetry and marginal homogeneity tests
n x n tables where there is one-to-one matching of cases and controls
Asymptotic symmetry and marginal homogeneity tests
Exact symmetry tests
Transmission disequilibrium test (TDT)
Kappa measure of interrater agreement
Two unique raters
Weights for weighting disagreements
Nonunique raters, variables record ratings for each rater
Nonunique raters, variables record frequency of ratings
Two-way table of frequencies
Brier score decomposition
Pharmacokinetics
Pharmacokinetic measures from time-and-concentration subject-level data
Tests that measurement is normally distributed
Analysis of data from crossover design experiment
Tests of bioequivalence for two treatments
U.S. Food and Drug Administration (FDA) submittals
Read and write data in the format required by the FDA for new drug application (NDA) submittals
Describe the contents of data written in the FDA required format
Produce an Installation Qualification (IQ) report
Receiver operating characteristic (ROC) analysis
Fit ROC regression models, with covariates
Calculate area under the curve
Calculate partial area under the curve
Obtain sensitivity for a given specificity, and vice versa
Test equality of ROC area against a “gold standard”
Šidák adjustment for multiple comparisons
Easy ROC curve plots for different classifiers and covariate values
ROC curve with simultaneous confidence bands
ICD-10 and ICD-9 codes
Designed for use with
The US National Center for Health Statistics (NCHS) ICD-10-CM diagnosis codes for healthcare encounter and claims data New
The US Centers for Medicare and Medicaid Services (CMS) ICD-10-PCS procedure codes for healthcare claims data New
The World Health Organization’s ICD-10 codes for morbidity and mortality reporting
NCHS ICD-9-CM diagnosis codes for healthcare encounter and claims data
CMS ICD-9-CM procedure codes for healthcare claims data
Suite of commands lets you:
Easily generate new variables based on codes
Indicators for different conditions
Short descriptions
Category codes from billable codes
And more
Verify that a variable contains valid codes and flag invalid codes
Standardize the format of codes
Interactive utilities let you
Look up descriptions for codes
Search for codes from keywords
ICD-10 and ICD-10-CM/PCS commands let you indicate the version of the codes in your dataset
Treatment Effects
Pharmacokinetics
Pharmacokinetic measures from time-and-concentration subject-level data
Tests that measurement is normally distributed
Analysis of data from crossover design experiment
Tests of bioequivalence for two treatments
Nonlinear mixed-effects models
Additional resources
An Introduction to Stata for Health Researchers, Fourth Edition by Svend Juul and Morten Frydenberg