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Epidemiology

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

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

U.S. Food and Drug Administration (FDA) submittals

Meta-analysis New

  • Effect sizes for binary and continuous outcomes
  • Common-effect, fixed-effects, and random-effects models
  • Forest plots, funnel plots, and more plots
  • Subgroup meta-analysis
  • Meta-regression
  • Small-study effects and publication bias
  • Cumulative meta-analysis

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
    • The US Centers for Medicare and Medicaid Services (CMS) ICD-10-PCS procedure codes for healthcare claims data
    • 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

Additional resources

See New in Stata 16 for more about what was added in Stata 16.

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