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Constant Stimuli (Condition List)

A Method that allows easy implementation of threshold estimation with the classical psychophysics method of Constant Stimuli. This method can also be used as a general-purpose condition list editor.

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The condition list table is organized such that each row beneath the header row represents a distinct condition to be tested within your experimental design. Each column corresponds to a unique variable, which refers to a parameter characterizing conditions in your experiment. For a comprehensive understanding of variables, refer to the


LabMaestro’s implementation of condition lists is generally agnostic to the intended use of variables in data analysis. However, the UI proposes four classes of variables used to refine the behaviour of a launched experiment during runtime. While the names of these classes guide their suggested use in implementing research design, they are not constraints.

Independent Variables

Independent Variables are the most commonly used Condition Variables. These are the parameters whose effects are of primary interest to the researcher, and which are manipulated across the experiment conditions. Typically, every subject will run the same combination of independent variable levels, although it is possible to implement larger designs by using Independent Split Variables (see next paragraph).

Independent Split Variables

Independent Split Variables share characteristics of Independent Variables; however, they are used in split designs (or between-subject designs) in which each test subject only contributes to a single combination of ISV levels. A second usage for ISV's is for implementing designs which contain too many conditions for a single subject to test, or for a single subject to test in a single session. In this case, the matrix of tested conditions can be easily partitioned into multiple subjects, or multiple sessions.

When clicking on Launch Experiment, LabMaestro will prompt the tester for the levels of the ISVs to be used for this subject.

Independent Blocked Variables

Independent Blocked Variables share characteristics of Independent Variables, with one additional 'blocking' feature. In this context, blocking ensures that all conditions within a specific level of the variable are completed before progressing to the next level.

Attribute Variables

Attribute Variables are parameters which provide further useful information about a condition, but which do not typically represent an independent variable. These parameters are usually implied by the levels of an Independent Variable, but are explicitly listed for clarity, simplicity, or for specific uses during the experiment. As an example, if an experiment requires a subject to enter a response to a stimulus, then the "Correct Response" could be included as an Attribute Variable. One reason for this would be to have a convenient place for a test condition to look, should the trial script need to take different paths based on a correct versus an incorrect response.

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