ii. potential errors in epidemiologic studies random error dr. sherine shawky
TRANSCRIPT
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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
n1
n2
n3
n4n5
n6
N
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Chance
Lack of Precision
Random Error
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Control of Random Error
PreventPrevent
StudyStudy
EvaluateEvaluate
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Prevention of Random Error
Sample sizeHypothesis
Type of Error
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Hypothesis
H0 = No difference
H1 = Some difference
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Study H0 in realityresults True False
Do notreject H0
Confidence level(1- )
Type IIerror
()Reject H0 Type I error
()Power(1-)
Types of Error
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n1 n2
N
Sample Size
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How many subjects are required ?
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Sample Size Calculation
Assumption ParametersFactors
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Assumption for Sample Size Calculation
H0 is not true & H1 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 testP-value
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Assumption for Statistical Testing
H0 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 CINot significant Significant
Mean/Proportion(one sample)
Value isincluded in CI
Value is notincluded in CI
Mean/Proportion(two samples)
Two CIsoverlap
Two CIs don’toverlap
Relativerisk/oddsratio
1.0 is includedin CI
1.0 is notincluded in CI
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ConclusionWhen 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.