For the latest COVID-19 campus news and resources, visit umassmed.edu/coronavirus.

Buscar Close Search
Buscar Close Search
Page Menu

USMLE | Biostatistics, Epidemiology/Population Health, & Interpretation of the Medical Literature

Epidemiology/population health

Measures of disease frequency: incidence/prevalence

Measures of health status: rates, crude and adjusted; reproductive rates (eg, maternal mortality, neonatal/infant/under-5 mortality); mortality, morbidity; standardization; life expectancy, health-adjusted life expectancy; population attributable risk (PAR), population attributable risk percent (PAR%); risk factors

Survival analysis interpretation (eg, Kaplan-Meier curve)

Composite health status indicators, measures of population impact: years of potential life lost; quality-adjusted life years; disability-adjusted life years; standardized mortality ratio

Population pyramids and impact of demographic changes

Disease surveillance and outbreak investigation: disease reporting; response to public

    • health advisory, health promotion; recognition of clusters

Communicable disease transmission: attack rate; herd immunity; reportable diseases

Points of intervention: primary, tertiary; community level (eg, cigarette taxes, soda taxes, smoke-free cities, buildings: restaurants, public buildings); school policies; access, healthy food, transportation, clean air, safe environments

Study design, types and selection of studies (includes dependent/independent variables)

Descriptive studies (case report [one person]/case series [more than one])

Analytical studies: observational: community surveys; cross-sectional (individuals); ecological (populations); case control; retrospective and prospective cohort

Analytical studies: interventional: clinical trial (randomized controlled trial; double-blind; placebo-controlled; noninferiority/equivalence trials); community intervention

Systematic reviews and meta-analysis: potential uses; estimation of effect sizes; heterogeneity; publication bias; forest plots, funnel diagrams; risk of bias, bias risk scale

Obtaining and describing samples: matching, inclusion/exclusion criteria, selecting appropriate controls for studies, lack of controls, concealed allocation, randomization, stratification

Methods to handle noncompliance: loss to follow-up; intention-to-treat analysis

Qualitative analysis

Measures of association

Relative risk

Odds ratio, hazard ratio

Other measures of association: number needed to treat/harm; absolute risk (AR), absolute risk percent (AR%); population attributable risk (PAR), population attributable risk percent (PAR%)

Distributions of data: measures of central tendency; measures of variability; regression to mean; normal distribution; nominal measurement

Correlation and regression, uses and interpretation: correlation coefficients; multiple regression

Principles of testing and screening

Properties of a screening test: validity, accuracy, reliability; criteria for a screening test; confirmatory testing; appropriateness; lead-time bias, length bias; screening vs diagnostic tests

Sensitivity and specificity; predictive value, positive and negative

ROC curves

Probability: theory (independence, product, addition rules); decision trees; likelihood ratios (application of Bayes theorem); post-test, pretest

Study interpretation, drawing conclusions from data

Causation: hypothesis-generating vs hypothesis-driven testing; causal criteria, temporality, temporal sequence, dose-response relationship; reverse causality

Chance

    • null hypothesis, Type I error and alpha level (multiple comparisons, random error/chance)
    • sample size and Type II error, beta, power
    • selection and interpretation of basic tests of statistical significance: chi-square;
    • confidence intervals; p-values; t-test
    • a priori vs. post hoc analysis: subgroup analysis; error rate; affect types

Interpretation of graphs/tables and text

Bias, confounding, and threats to validity (includes methods to address)

    • selection, sampling bias
    • information bias: recall; ascertainment, ecologic fallacy, lack of blinding; loss to follow up confounding variables, Hawthorne effect (includes methods to address)
    • other threats to validity (eg, placebo effect)

Internal vs. external validity: generalizability (external validity); efficacy vs effectiveness

Statistical vs. clinical significance; clinical and surrogate outcome/end-point

Clinical decision making, interpretation and use of evidence-based data and recommendations: application of study results to patient care and practice, including patient preferences and individualization of risk profiles; risk/benefit analysis; synthesis of concepts with real data

Research ethics

Informed consent for research

Privacy of patient data (HIPAA)

Roles of institutional review boards (IRBs)

Intervention analysis: interim analysis; stopping analysis; safety monitoring

Regulatory issues: drug development, phases of approval; appropriateness of placebo; appropriateness of randomized clinical trial; components of studies; ethics; scheduling; off-label use

Other issues related to research ethics


Copyright © 2015 by the Federation of State Medical Boards of the United States, Inc. (FSMB) and the National Board of Medical Examiners® (NBME®). All rights reserved. Printed in the United States of America. The United States Medical Licensing Examination® (USMLE®) is a joint program of the FSMB and the NBME.