Epi
Experimental Error
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Experimental Error
, Experimental Bias
Definitions
Bias
Error introduced systematically by faults in experimental methodology
Experimental Error
Error due to either bias (see below)
Error due to chance (random)
Alpha Error (
False Positive
)
Difference is due to chance
P Value represents the probability that results are due to chance (p <0.05 is goal)
Beta Error (
False Negative
)
There was a true difference between experimental and control groups
However, study detects no difference between experimental and control groups
Typically results from too small a sample size
Statistical power measures the study ability to detect a
Statistically Significant
difference
Validity
Internal Validity
Reliable experimental methodology reduces error due to chance and bias
External Validity
Experimental results are generalizable to real-world scenarios
Clinically Significant
improved outcomes
Types
Bias
Selection Bias
http://en.wikipedia.org/wiki/Selection_bias
Patient
Selection Bias
Subjects chosen for study are not randomly selected or otherwise not correctly selected
Measurement Bias
https://learner.org/courses/learningmath/data/session1/part_c/index.html
Inconsistent or incorrect measurement
Assessment Bias (ascertainment bias, diagnostic bias, detection bias)
Subjects are affected by their opinions about the system (often due to inadequate blinding)
Allocation Bias
Additional difference between the intervention and control groups
Beyond the intervention (inadequate randomization)
Hawthorn
e Effect
People perform better when they know they are being observed Checklist Effect
Checklists aid decision making and may skew results
References
Hersh (2014) Evaluation of Clinical Information Systems, AMIA’s CIBRC Online Course
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