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Potential Errors In Epidemiologic Studies

Potential Errors In Epidemiologic Studies. Random Error. II. Dr. Sherine Shawky. Learning Objectives. Understand the concept of random error Recognize the methods to prevent random error Know the methods to evaluate the role of chance on results. Performance Objectives.

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Potential Errors In Epidemiologic Studies

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  1. Potential Errors In Epidemiologic Studies Random Error II. Dr. Sherine Shawky

  2. Learning Objectives • Understand the concept of random error • Recognize the methods to prevent random error • Know the methods to evaluate the role of chance on results

  3. Performance Objectives • Improve precision • Evaluate the role of chance

  4. In most epidemiologic studies, it is impossible to evaluate every member of the entire population. Thus, the relationship between exposure and health-related event is judged from observations on sample of the population

  5. Samples n2 n6 n1 n4 n5 n3 N

  6. Chance Random Error Lack of Precision

  7. Control of Random Error Prevent Study Evaluate

  8. Prevention of Random Error Sample size Hypothesis Type of Error

  9. Hypothesis H0 = No difference H1 = Some difference

  10. Types of Error

  11. Sample Size n1 n2 N

  12. How many subjects are required ?  

  13. Sample Size Calculation Assumption Parameters Factors

  14. Assumption for Sample Size Calculation H0 is not true & H1 is true

  15. Factors for Sample Size Calculation • Population size • Research question • Study design • Type of data

  16. Parameters for Sample Size Calculation • Probability of type I error • Probability of type II error • Proportion of population that are exposed to, or have health-related event • Magnitude of the expected effect

  17. What is the power of this study if only these subjects are available ?         ? Power

  18. Power Calculation Work the appropriate sample size equation in the inverse direction, using the available sample size

  19. Evaluation of the Role of Chance Statistical Testing Confidence Interval

  20. Statistical Testing Assumption P-value Statistical test

  21. Assumption for Statistical Testing H0 is true

  22. Choice of Statistical Test • Research question • Type of data • Characteristics of data

  23. P-value • The P-value is the estimated value for  issue from results • The P-value depends on the sample size and the strength of the association

  24. P-value (cont.) • Two-tailed for given magnitude and uncertain direction • One tailed for given magnitude and known direction

  25. Confidence Interval(CI) • More informative than P-value • Indicates presence or absence of statistical significance • Calculated for mean, proportion, relative risk and odds ratio

  26. Interpretation of CI

  27. Conclusion When a research is performed on a sample of the population, the researcher has to minimize the role of chance before initiating the study. Also, he should evaluate its impact on the results before making decisions.

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