How to conduct a meta analysis
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How to Conduct a Meta-Analysis - PowerPoint PPT Presentation

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How to Conduct a Meta-Analysis. Arindam Basu MD MPH About the Author Required Browsing. Objectives. Following the course, you will be able to : Define Meta-analysis Select Studies for a Meta-analysis Identify different types of Models Calculate Summary Effects

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How to conduct a meta analysis l.jpg

How to Conduct a Meta-Analysis

Arindam Basu MD MPH

About the Author

Required Browsing

Objectives l.jpg

Following the course, you will be able to:

  • Define Meta-analysis

  • Select Studies for a Meta-analysis

  • Identify different types of Models

  • Calculate Summary Effects

  • Interpret Results of a Meta-analysis

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What is Meta-analysis?

  • Synthesis of previous studies

  • Providing a Summary estimate

  • Steps

    • Identify studies

    • Define Eligibility Criteria

    • Abstract Data

    • Do Statistical Analysis

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Identify Studies: Overview

  • Steps:

    • Search Your Personal Files First

    • Search Electronic Databases

    • Review Reference Lists of Articles

    • Contact Experts and Researchers

    • Retrieve New Articles

  • Evaluate Quality of the Studies

  • Set Up Eligibility Criteria

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Searching Electronic Databases

  • First, Define a Search Strategy

  • Limitations of Databases

    • incomplete and imperfect queries

    • language problems

    • problems with fugitive literature

  • Publication Bias is important

    • What is publication bias

    • How to deal with publication bias

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Evaluating Study Quality

  • Define Study Quality Criteria Early

  • Set Up A Good Scoring System

  • Develop A Form for Assessment

  • Calculate Quality for each Study

  • Use this for Sensitivity Analysis

    • stratify studies according to quality

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Defining Eligibility of Studies

Select Eligible Studies Based On:

  • Study Designs

  • Years of Publication

  • Language

  • Choice among multiple articles

  • Sample-size or follow-up issues

  • Similarity of Exposure and/or Rx

  • Completeness of information

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Abstract Data - Review!


  • Identify Relevant Articles

  • Sort out Eligible Articles

  • Set up a Form for Abstraction

  • Enter the Eligible Studies

  • Use this as your database

    Statistical Analysis is next...

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Statistical Analysis - Overview

  • Select An Estimate of Effect

  • Choose An Effects Measure

  • Select An Effects Model

  • For Each Model:

    • Calculate Summary Effect Size

    • Calculate Confidence Intervals

    • Calculate Q-statistic for Homogeneity

  • Perform Sensitivity Analysis

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Selecting Estimate of Effect

  • Choose Only One Estimate

  • For RCTS, choose the one with

    • Once randomized always randomized

  • For nonrandomized trials, choose:

    • estimate adjusted only for age

    • that, and for a known confounder

    • the “most adjusted” estimate

    • estimate presented in the abstract

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Choosing An Effect Measure

  • RCTs or Cohort Studies

    • Rate Difference between Treatment and Control Groups

    • Ratio of Disease Rates

  • Case Control Studies

    • Odds’ Ratio

    • Rate Ratio

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Selecting An Effects Model

  • Available Types:

    • Fixed Effects Model

    • Random Effects Model

  • Difference Between the Two

  • Special Cases:

    • When Outcomes are not binary

  • Methods to be Used for them

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Fixed Effects Model

  • Methods:

    • Mantel Haenszel Method

    • Peto’s Method

    • General Variance Based Methods

      • For Rate Difference

      • For Rate Ratios

      • When only RR and 95 CI given

  • Tests of Homogeneity

    • Calculation of Q Statistic

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Mantel Haenszel Method

  • Download Spreasheet Calculator

  • Strength of Mantel Haenszel

    • Very powerful

    • Widely Used

  • Limitation

    • Cannot Control For Confounding!

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Peto’s Method

  • Similar to Mantel Haenszel

  • Download Calculator

  • Simpler Computation

  • No Control for Confounding

  • Good for RCTs

  • Requires 2 X 2 Table

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Variance-Based Methods

  • Download Calculators For:

    • Rate Difference

    • For only Relative Risk and 95% CI

  • Strengths and Limitations

    • Good For Rate Differences

    • Computationally Intensive

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Tests of Homogeneity

  • Establish Null Hypothesis that Effect Sizes Are Equal in All of the Studies [FAIL TO REJECT NULL]

  • Tested By Using Q-statistic

  • Q-statistic is distributed as chi-square distribution with degree of freedom = n-1 where n = number of studies

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Random Effects Model

  • Download The Calculator!

  • Strengths and Limitations:

    • Can Generalize the Conclusions

    • Computationally Intensive

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Continuous Outcomes

  • Measurement Scale: Continuous

  • Outcome Measured in Same Scale

    • Download Spreadsheet Calculator!

  • Essentially Extension of ANOVA

  • Useful For Integrating Social Science Research Data

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Sensitivity and Publication Bias

  • Conduct Sensitivity Analysis

    • Stratify studies by their quality rating

    • Compare Fixed and Random Effects

  • Deal With Publication Bias

    • Construct A Funnel Plot

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  • Presentation of Meta-analysis or Literature Synthesis

  • Download The Graph Maker

  • More Resources...