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EPID 623-88 Introduction to Analysis and Interpretation of HIV/STD Data. Epidemiologic Study Designs—a review Manya Magnus, Ph.D. Summer 2001. Objectives. To review epidemiologic study designs To review measures of association used in epidemiologic studies - PowerPoint PPT Presentation
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EPID 623-88 Introduction to Analysis and
Interpretation of HIV/STD Data
Epidemiologic Study Designs—a review
Manya Magnus, Ph.D.Summer 2001
Objectives
• To review epidemiologic study designs• To review measures of association
used in epidemiologic studies• To discuss interpretation of study
results
Basic study designsAnalytic
Descriptive Observational Intervention
Case reports/series Cross-sectional
Randomized controlled trials
Birth cohorts
Cohort (concurrent, non-
concurrent)
Community-based
interventions
Ecologic/correlational
Case-control (and variations)
Case reports/case series (1)
• Description of unique, unusual, rare events in one or several individuals
• Often used by physicians• May stimulate awareness of problem
(note: PCP, DES/vaginal clear cell adenocarcinoma), hypothesis generating
Case reports/case series (2)
• Analysis of case series:– Might focus on incidence or prevalence in
general (or target) population– Raw data, small numbers– If more than a few, proportions (5/10=50%)– Narrative as essence of report, plus
communication of context, why interesting
Birth cohorts
• Allows exploration of trends based on age or period effects
• Allows exploration of cumulative effects of exposure, latency periods, timing of exposure
• Explore cohort effects, age effects, period effects
• Interaction between time and calendar age• Looking graphically at cross-sectional data by
age group
Ecologic studies
• Aggregate measures• Environmental measures• Global measures• Units of observation generally geographic region,
area• Looking at number of outcome events and
predictors of interest on aggregate level• “Ecologic fallacy” issues• Evaluation of association: plotting, comparison of
rates, prevalence, adjusted-measures, etc.
Cross-sectional studies
• Individual-level data• “Snapshot” of exposure and outcome• No temporality provided• No causation can be inferred• Useful in hypothesis generating• Analysis: frequencies, cross-tabs, point
prevalence rate ratio, odds ratio, comparison of rates, etc.
Cohort studies
• Concurrent or non-concurrent• “gold standard” for observational studies• Basis for other designs• Disease-free at baseline• Follow for outcome• Analysis: frequencies, cross-tabs, relative
risk, hazard ratio, attributable risk, etc.
Case-control studies
• Look at those with/without outcome of interest and evaluate exposures
• Good for rare diseases• Many variations (nested, case-cohort,
etc.)• Analysis: frequencies, cross-tabs, odds
ratio, attributable risk, etc.
Randomized controlled clinical trials
• Cohort studies based on model of RCT• Randomize subjects to receive
intervention and follow for outcome(s) of interest
• Intent-to-treat analysis• Analysis: frequencies, cross-tabs,
relative risk, hazard ratio, etc.
Community-based interventions
• Similar to RCT, but randomizing communities
• Unit of analysiscommunity (note power issues)
Reminders (1)Diseased Not
diseased
Exposed A B A+B
Not exposed
C D C+D
A+C B+D A+B+C+D
Reminders (2)
Relative risk (RR) formula
[A/(A+B)]/[C/(C+D)]
Reminders (3)
Odds ratio (OR) formula
AD/BC
Interpreting published results
Steps to understanding published tables
1. What is the study design?
Steps to understanding published tables
1. What is the study design?
2. What is unit of analysis?
Steps to understanding published tables
1. What is the study design?2. What is unit of analysis?
3. What are predictors of interest?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?
4. What are outcomes of interest?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?
5. In tables, what is n?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?
6. Is the table referring to subset or whole sample?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?
7. What is being presented, compared?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?
8. What are the denominators? Do they differ by column?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?
9. Can you add up data from text?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?
9. Can you add up data from text? 10. Can you calculate measures of association?
Do they agree with the authors’?
Steps to understanding published tables
1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?9. Can you add up data from text? 10. Can you calculate measures of association? Do they agree
with the authors’?
11. Are the authors’ conclusions correct?