T

Test of association
A statistical test to assess whether the value of one variable is associated (i.e. varies with) the value of another variable, or whether the presence or absence of a factor is more likely when a particular outcome is present. See also correlation.

Time to event
A description of the data in studies where the analysis relates not just to whether an event occurs but also when. Such data are analysed using survival analysis.  (Also called survival data.)

Tolerability
[of an intervention:] usually refers to medically less important (that is, without serious or permanent sequelae), but unpleasant adverse effects of drugs. These include symptoms such as dry mouth, tiredness, etc, that can affect a person’s quality of life and willingness to continue the treatment. As these adverse effects usually develop early on and are relatively frequent, randomised controlled trials may yield reliable data on their incidence.

Toxicity
The degree to which a medicine is poisonous. How much of a medicine can be taken before it has a toxic effect.

Treatment
The process of intervening on people with the aim of enhancing health or life expectancy. Sometimes, and particularly in statistical texts, the word is used to cover all comparison groups, including placebo and no treatment arms of a controlled trial and even interventions designed to prevent bad outcomes in healthy people, rather than cure ill people. See also intervention, experimental intervention and control.

Treatment effect
See estimate of effect

Trend

1. A consistent movement across ordered categories, e.g. a change in the effect observed in studies grouped according to, for instance, intensity of treatment.
2. Used loosely to refer to an association or possible effect that is not statistically significant.  This usage should be avoided.

Trialist
Used to refer to a person conducting or publishing a controlled trial.

Type I error
A conclusion that a  treatment works, when it actually does not work. The risk of a Type I error is often called alpha. In a statistical test, it describes the chance of rejecting the null hypothesis when it is in fact true. (Also called false positive.)

Type II error
A conclusion that there is no evidence that a treatment works, when it actually does work. The risk of a Type II error is often called beta. In a statistical test, it describes the chance of not rejecting the null hypothesis when it is in fact false.  The risk of a Type II error decreases as the number of participants in a study increases. (Also called false negative.)