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Absolute risk difference
See risk difference.

Absolute risk reduction
See risk difference.

Additive model
A statistical model in which the combined effect of several factors is the sum of the effects produced by each of the factors in the absence of the others. For example, if one factor increases risk by a% and a second factor by b%, the additive combined effect of the two factors is (a + b)%. See also multiplicative model.

Adjusted analysis
An analysis that controls (adjusts) for baseline imbalances in important patient characteristics.

Adverse event
An adverse outcome that occurs during or after the use of a drug or other intervention but is not necessarily caused by it.

Adverse effect
An adverse event for which the causal relation between the drug/intervention and the event is at least a reasonable possibility. The term ‘adverse effect’ applies to all interventions, while ‘adverse drug reaction’ (ADR) is used only with drugs. In the case of drugs an adverse effect tends to be seen from the point of view of the drug and an adverse reaction is seen from the point of view of the patient.

Adverse reaction
See adverse effect.

Aggregate data
Data summarised by groups, for example summary outcome data for treatment and control groups in a controlled trial.

Allocation concealment
See concealment of allocation.

Applicability (synonyms: external validity, generalisability, relevance, transferability)
The degree to which the results of an observation, trial or review hold true in other settings.

Arm
[In a controlled trial.] Refers to a group of participants allocated a particular treatment. In a randomised controlled trial, allocation to different arms is determined by the randomisation procedure. Many controlled trials have two arms, a group of participants assigned to an experimental intervention (sometimes called the treatment arm) and a group of participants assigned to a control (the control arm). Trials may have more than two arms, with more than one experimental arm and/or more than one control arm.

Association
A relationship between two characteristics, such that as one changes, the other changes in a predictable way. For example, statistics demonstrate that there is an association between smoking and lung cancer. In a positive association, one quantity increases as the other one increases (as with smoking and lung cancer).  In a negative association, an increase in one quantity corresponds to a decrease in the other. Association does not necessarily imply a causal effect.  (Also called correlation.)

Attrrition
The loss of participants during the course of a study. (Also called loss to follow up.) Participants that are lost during the study are often call dropouts.

Attrition bias
Systematic differences between comparison groups in withdrawals or exclusions of participants from the results of a trial. For example, patients may drop out of a trial because of side effects of the intervention.Excluding these patients from the analysis could result in an overestimate of the effectiveness of the intervention.