Study design where treatments, interventions, or enrollment into different study groups are assigned by
random allocation rather than by conscious decisions of clinicians or patients. If the sample size
is large enough, this study design avoids problems of bias and confounding variables by assuring
that both known and unknown determinants of outcome are evenly distributed between treatment and
control groups.
Systematic error due to the differences in accuracy or completeness of recall to memory of past events
or experiences.
The sequence of referrals that may lead patients from primary to tertiary centers raises the proportion
of more severe or unusual cases, thus increasing the likelihood of adverse or unfavorable outcomes.
The ratio of the probability of developing, in a specified period of time, an outcome among those receiving the treatment of interest or exposed to a risk factor, compared with the probability of developing the outcome if the risk factor or intervention is not present (i.e., the ratio of risk in the treated group to the risk in the control group: RR=EER/CER).
The extent to which a treatment reduces a risk, in comparison with patients not receiving the treatment
of interest (i.e., the percent reduction in events in treated compared to controls: RRR=[(CER-EER)/CER]).
Study design in which cases where individuals who had an outcome event in question are collected and
analyzed after the outcomes have occurred.
Patient characteristics or factors associated with an increased probability of developing a condition
or disease in the first place. Compare with prognostic factors. Neither risk or prognostic factors
necessarily imply a cause and effect relationship.
The ratio of risk in the treated group (EER) to the risk in the control group (CER). This is used in
randomized trials and cohort studies and is calculated as EER/CER.
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Duke University
Last modified on: 16-Dec-04