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

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II. Potential Errors In Epidemiologic Studies Random Error 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 Improve precision Evaluate the role of chance

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

Samples n1n1 n2n2 n3n3 n4n4 n5n5 n6n6 N

Chance Lack of Precision Random Error

Control of Random Error Prevent Study Evaluate

Prevention of Random Error Sample size Hypothesis Type of Error

Hypothesis H 0 = No difference H 1 = Some difference

Types of Error

n1n1 n2n2 N Sample Size

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

Sample Size Calculation Assumption Parameters Factors

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

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

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

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

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

Evaluation of the Role of Chance Statistical Testing Confidence Interval

Statistical Testing Assumption Statistical test P-value

Assumption for Statistical Testing H 0 is true

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

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

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

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

Interpretation of CI

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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