方法对比

	Mouse-Tracking Paradigm	Within-Subjects Factorial Design
领域	社会心理学	社会心理学
方法族	Process / pipeline	Process / pipeline
起源年份	2010	2004
提出者	Jonathan Freeman & Nalini Ambady	Experimental-design tradition (widely used in social psychology)
类型	Process-tracing reaction-method	Experimental design framework
开创性文献	Freeman, J. B., & Ambady, N. (2010). MouseTracker: Software for studying real-time mental processing using a computer mouse-tracking method. Behavior Research Methods, 42(1), 226-241.	Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The Day Reconstruction Method. Science, 306(5702), 1776-1780.
别名	Mouse Tracking, Hand-Trajectory Tracking, MouseTracker Paradigm	Repeated-Measures Factorial Design, Within-Participants Factorial, Crossed Within-Subjects Design
相关	3	2
摘要	The mouse-tracking paradigm, popularized by Freeman and Ambady's 2010 MouseTracker software, uses the continuous trajectory of hand movements during a choice to reveal the real-time dynamics of cognition. Participants begin each trial with the cursor at the bottom of the screen and move it to one of two response options in the upper corners; the software records the streaming x- and y-coordinates of the cursor throughout the movement. Because the hand can begin moving before a decision is fully resolved, the curvature of the trajectory toward the unchosen option indexes the degree to which that alternative was simultaneously activated -- a graded, moment-by-moment signature of competition and conflict that a final button press cannot show. Mouse tracking became a popular, inexpensive process-tracing method in social cognition, used to study the dynamics of categorization, evaluation, stereotyping, and decision making as they unfold.	The within-subjects factorial design is an experimental framework in which each participant is exposed to every combination of two or more manipulated factors, allowing researchers to test the main effect of each factor and their interactions while using each person as their own control. Because the same individuals experience all conditions, between-subject differences are removed from the error term, giving within-subjects factorial designs substantially greater statistical power and efficiency than between-subjects designs for the same number of participants. This makes them a workhorse of experimental social psychology, especially for reaction-time, judgment, and affect studies where many trials per person are feasible. The design's power comes with the need to control order and carryover effects through counterbalancing, and to analyze the data with repeated-measures or mixed-effects models that respect the non-independence of observations from the same person.