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

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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

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Performance Objectives Improve precision Evaluate the role of chance

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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

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Samples n1n1 n2n2 n3n3 n4n4 n5n5 n6n6 N

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Chance Lack of Precision Random Error

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Control of Random Error Prevent Study Evaluate

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Prevention of Random Error Sample size Hypothesis Type of Error

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Hypothesis H 0 = No difference H 1 = Some difference

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Types of Error

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n1n1 n2n2 N Sample Size

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How many subjects are required ?

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Sample Size Calculation Assumption Parameters Factors

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Assumption for Sample Size Calculation H 0 is not true & H 1 is true

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

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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

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What is the power of this study if only these subjects are available ? ? Power

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

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Evaluation of the Role of Chance Statistical Testing Confidence Interval

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Statistical Testing Assumption Statistical test P-value

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Assumption for Statistical Testing H 0 is true

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Choice of Statistical Test Research question Type of data Characteristics of data

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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

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

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

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Interpretation of CI

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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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Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.

Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.

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