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An outcome measure, endpoint, effect measure or measure of effect is a measure within medical practice or research, (primarily clinical trials) which is used to assess the effect, both positive and negative, of an intervention or treatment. [1] [2] Measures can often be quantified using effect sizes. [3]
The reliability (statistics) and validity (statistics) of any measure of health status must be known so that their impact on the assessment of health outcomes can be taken into account. In mental health services these values may be quite low, especially when carried out routinely by staff rather than by trained researchers, and when using short ...
The average treatment effect (ATE) is a measure used to compare treatments (or interventions) in randomized experiments, evaluation of policy interventions, and medical trials. The ATE measures the difference in mean (average) outcomes between units assigned to the treatment and units assigned to the control.
The measure of effects depends on the intervention being considered. Examples include the number of people cured of a disease, the mm Hg reduction in diastolic blood pressure and the number of symptom-free days experienced by a patient. The selection of the appropriate effect measure should be based on clinical judgment in the context of the ...
Core outcome sets are commonly used by clinical investigators who conduct clinical trials for the treatment of a health condition. [2] [3] [4] The patient population associated with a particular core outcome set may vary, as some apply to all patients with that health condition and others apply to a small subset of that population. [2]
CORE-OM [1] [2] (Clinical Outcomes in Routine Evaluation-Outcome Measure) [3] is a common self-report measure of global distress. It can be used as an initial screening tool and as an assessment tool of the response to psychological therapy .
The minimal important difference (MID) or minimal clinically important difference (MCID) is the smallest change in a treatment outcome that an individual patient would identify as important and which would indicate a change in the patient's management.
Estimation statistics, or simply estimation, is a data analysis framework that uses a combination of effect sizes, confidence intervals, precision planning, and meta-analysis to plan experiments, analyze data and interpret results. [1]