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.