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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
n1
n2
n3
n4n5
n6
N
Chance
Lack of Precision
Random Error
Control of Random Error
PreventPrevent
StudyStudy
EvaluateEvaluate
Prevention of Random Error
Sample sizeHypothesis
Type of Error
Hypothesis
H0 = No difference
H1 = Some difference
Study H0 in realityresults True False
Do notreject H0
Confidence level(1- )
Type IIerror
()Reject H0 Type I error
()Power(1-)
Types of Error
n1 n2
N
Sample Size
How many subjects are required ?
Sample Size Calculation
Assumption ParametersFactors
Assumption for Sample Size Calculation
H0 is not true & H1 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 testP-value
Assumption for Statistical Testing
H0 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 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
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.