Terms used in rtprep

The vocabulary the rest of the documentation assumes, defined once.

Response times and what contaminates them

Contaminant: A trial not produced by the decision process the experiment is about: a response made before the stimulus was read, one delayed by something outside the task, one made without using the evidence. The word is used for the trial, not for the statistical criterion that might catch it; "outlier" is kept for the criterion and for literature that uses it that way. rtprep names three processes, and r_contaminated() generates each: leading-edge anticipations, delayed start-ups, and informationless responses.
Leading edge: The fast rising flank of a response time distribution, the short climb from the fastest response to the mode. It matters because a right-skewed distribution has almost no mass there, so a trial that arrives early sits well inside a criterion built around the mean and is not removed by one.

Screening: Classifying trials, deciding which came from the decision process. rt_screen() screens.
Trimming: Screening that then removes what it flagged. Every trimming rule screens; not every screening rule trims, since a probability can be carried forward as a weight instead.
Aggregation: Turning the surviving trials into summary statistics. rt_summary() aggregates. Kept separate from the two above because a screen and a summary fail in different ways, and the choice between them is a real one.

Evidence accumulation model (EAM): A model of choice and response time in which a decision is made by gathering evidence over time until enough has arrived to commit. The diffusion model (DDM) is one member, a racing accumulator another.
Drift: How fast evidence arrives, on average; the rate of the accumulation. Higher drift means faster and more accurate responding.
Bound: How much evidence is required before committing, also called boundary separation. A wider bound means slower and more accurate responding, which is where speed-accuracy trade-offs live.
Non-decision time (ndt): Everything in a response time that is not evidence accumulation: encoding the stimulus at one end, executing the movement at the other.
EZ-diffusion: A closed-form inversion from the mean response time, its variance, and accuracy to drift, bound and ndt, so no fitting is needed. rt_summary() produces the three inputs and ez_ddm() does the inversion.