Epidemiology study designs

Mind Map by jillian.kowalchuk, updated more than 1 year ago
Created by jillian.kowalchuk about 6 years ago


Mind Map on Epidemiology study designs, created by jillian.kowalchuk on 05/01/2014.

Resource summary

Epidemiology study designs
1 Ecological
1.1 Features
1.1.1 Advantages If data is difficult to measure at an individual level To study group-sepcific events When data are readily available Quick Less costly
1.1.2 Disadvantages Cannot infer causality Confounders likely
1.1.3 Population-based
1.1.4 Prevalence or incident cases
1.1.5 Data Collection Routine data sources Vital registration data Demographic data Disease registries
1.1.6 Analysis Standardization Direct Standardized Rate Indirect SMR
1.1.7 Interpretation Ecological fallacy Bias Mixing/Migration Confounding
1.1.8 Study Design Time-trend design Mixed studies Multi-group study
2 Cross-sectional
2.1 Features
2.1.1 Advantages Rapid Easy to collect/analyse Relatively cheap Can help policy to see how many ppl need treatment May be possible to assume causality if exposure constant (i.e. genetics) May be only plausible study design to answer question
2.1.2 Disadvantages Did exposure precede outcome (information bias)? Medium probability of selection bias Medium confounding Causality not possible in exposures that change (i.e. diet) Can't see time relationship or incidence rate
2.1.3 Study Design Descriptive Estimate the frequency of outcomes or exposure without the intention of investigating causal associations. Individual level data on outcome, exposure or both Secular Seasonal Analytical Collects data on both outcome and exposure at the same time-point for a given study subject. Good for testing hypothesize of association where exposure status does not change over time.
2.1.4 Sampling Questionnaires Pilot study
2.2 Data collection
2.2.1 Period Prevalence
2.2.2 Point Prevalence
2.3 Interpretation
2.3.1 Reverse causality
2.4 Analysis
2.4.1 **Prevalence Ratio
2.4.2 Outcome rare= odds ratio
3 Cohort Studies
3.1 Features
3.1.1 Advantages Low selection bias Low recall bias Low confounding
3.1.2 Disadvantages Loss to follow up Logistically difficult Expensive
3.1.3 Study Design Descriptive Observational Analytical Prospective Retrospective Sampling Occupational cohort Analysis Descriptive Risk or rate Analytical Risk, rate, attributable risk, attributable fraction, population attributable risk, population attributable fraction Time-series analysis Data collection Retrospective= routine sources Prospective = exposures that aren't going to change
3.1.4 Interpretation Confounding/bias Loss to follow up Observer bias
3.1.5 Screening method Lead-time bias Length-time bias
4 Case Control
4.1 Features
4.1.1 Sampling Case definition Inclusion/exclusion criteria
4.1.2 Data Collection Almost always retrospective Reporting bias
4.1.3 Advantages Low loss-to follow up Rapid
4.1.4 Disadvantages Selection bias Information bias Confounding
4.1.5 Study Design Matching Nested case-control Overmatching Individual matching Frequency matching Control
4.1.6 Analysis Odds ratio of exposure Outcome rare measure approximates risk ratio
4.1.7 Interpretation Watch for discussed biases and confounders Reverse causality
4.1.8 Screening method Selection bias Information bias
5 Intervention
5.1 Advantages
5.1.1 Low selection bias
5.1.2 Low information bias
5.1.3 Low Confounding
5.1.4 Infer causality
5.2 Disadvantages
5.2.1 Loss to follow up
5.2.2 More complex
5.2.3 Expensive
5.3 Features
5.3.1 Study Design Ethical approval Declaration of Helsinki Efficacy Effectiveness Plausability studies Historical controls Geographical controls Opportunistic controls RCT Cluster-randomized trials Factorial design Crossover design Non-randomized trial selection bias
5.3.2 Sampling Representative population Choice of Control Allocation Simple randomization Systematic randomization Blocked Randomization Stratified randomization Matched-pair randomization Envelopes (allocation concealment) Minimization Blinding Single Double blinded Gold standard: Double-blinded randomized placebo-controled trial ascertainment bias
5.3.3 Data Collection Same as Cohort and Cross-sectional
5.3.4 Analysis Intervention allocation Interim analysis Intention-to-treat v.s per-protocol Intervention efficacy
5.3.5 Interpretation Bias and confounders
5.3.6 Screening methods Information bias Misclassification bias
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