@article{
 title = {Advanced mouse-tracking analytic techniques for enhancing psychological science Basic Paradigm},
 type = {article},
 identifiers = {[object Object]},
 keywords = {computer mouse-tracking,face perception,impression formation,person perception},
 pages = {1-18},
 id = {8f7c6176-273a-3fd1-8afe-6ec5087b6955},
 created = {2017-09-01T15:53:50.831Z},
 file_attached = {true},
 profile_id = {80da7853-f7b7-36a9-8e4c-d7ddb2d9e538},
 group_id = {a2333ea3-15a4-3d40-8d36-f0d9590ca926},
 last_modified = {2017-09-01T15:53:50.928Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 abstract = {" The best laid plans of mice and men often go awry. " (Burns, 1785) And often, going awry is psychologically mean-ingful. Recent advances in psychological science have shown that motion trajectories reflect underlying cognitive processes. In the current article, we discuss how analysis of computer mouse-trajectories and their temporal dynamics can provide powerful insight into these processes. Our goal is to describe how researchers might incorporate mouse-tracking into their psycholog-ical toolbox such that they can address novel hypotheses within their areas of research. We pri-marily focus on recently developed advanced Abstract Computer mouse-tracking is a relatively recently developed behavioral methodology that can contribute unique insight into a wide variety of psychological phenomena. By recording mouse movements en route to specific responses on a screen, researchers glean continuous information about tentative commitments to multiple response alternatives over time. This approach yields a richness of data that can be fully explored with a variety of sophisticated analytic techniques, but these approaches are relatively underutilized and can be difficult to adopt. Here we describe several techniques for researchers to examine the onset and timing of evolving decision processes; test the degree of response competition at different time points; assess trajectory complexity with spatial disorder analyses; identify qualitatively distinct psychological processes during response generation; and finally to distill unique and meaningful components from mouse-tracking data for subsequent analysis. With this guide, we hope researchers can address novel hypotheses otherwise inaccessible with more traditional methods. analytic techniques that capitalize on the richness of data provided by a mouse-tracking approach. First, to provide a larger framework conducive for understanding, we discuss the basic paradigm, the theoretical principles underlying the method, and provide examples of what novel hypotheses this technique has already been used to test. [AQ: 1][AQ: 2][AQ: 3] We then provide step-by-step instructions for researchers to analyze the high-resolution tempo-ral data provided by mouse-tracking with several techniques, and how these data might be analyzed to address unique questions that would otherwise be unanswerable with more traditional measures. Namely, we focus on (a) time course analyses of mouse-trajectory coordinates, useful in examin-ing how various factors exert influence on or are integrated into the evolving decision process over time; (b) examination of velocity and accelera-tion, which can index the degree of response competition at different time points; (c) assess-ment of spatial disorder in trajectories, indicative of complexity and unpredictability associated with response dynamics; (d) the identification of smooth versus abrupt response competition, which can yield important insights into the pres-ence of more dynamic versus more discrete-like cognitive processes; and finally, (e) principle com-ponents analysis (PCA), which can distill unique and meaningful components from the mouse-tracking data for subsequent analysis. Because of our own work with mouse-tracking, many of the examples will be drawn from the person percep-tion and social categorization literature, but we stress that the methodology is readily applicable to diverse domains},
 bibtype = {article},
 author = {Hehman, Eric and Stolier, Ryan M and Freeman, Jonathan B and Freeman, Jon},
 journal = {Group Processes & Intergroup Relations}
}

{"_id":"vTCEwYTKjgqWC3rTt","bibbaseid":"hehman-stolier-freeman-freeman-advancedmousetrackinganalytictechniquesforenhancingpsychologicalsciencebasicparadigm","downloads":0,"creationDate":"2017-09-01T15:59:40.262Z","title":"Advanced mouse-tracking analytic techniques for enhancing psychological science Basic Paradigm","author_short":["Hehman, E.","Stolier, R., M.","Freeman, J., B.","Freeman, J."],"year":null,"bibtype":"article","biburl":null,"bibdata":{"title":"Advanced mouse-tracking analytic techniques for enhancing psychological science Basic Paradigm","type":"article","identifiers":"[object Object]","keywords":"computer mouse-tracking,face perception,impression formation,person perception","pages":"1-18","id":"8f7c6176-273a-3fd1-8afe-6ec5087b6955","created":"2017-09-01T15:53:50.831Z","file_attached":"true","profile_id":"80da7853-f7b7-36a9-8e4c-d7ddb2d9e538","group_id":"a2333ea3-15a4-3d40-8d36-f0d9590ca926","last_modified":"2017-09-01T15:53:50.928Z","read":false,"starred":false,"authored":false,"confirmed":false,"hidden":false,"abstract":"\" The best laid plans of mice and men often go awry. \" (Burns, 1785) And often, going awry is psychologically mean-ingful. Recent advances in psychological science have shown that motion trajectories reflect underlying cognitive processes. In the current article, we discuss how analysis of computer mouse-trajectories and their temporal dynamics can provide powerful insight into these processes. Our goal is to describe how researchers might incorporate mouse-tracking into their psycholog-ical toolbox such that they can address novel hypotheses within their areas of research. We pri-marily focus on recently developed advanced Abstract Computer mouse-tracking is a relatively recently developed behavioral methodology that can contribute unique insight into a wide variety of psychological phenomena. By recording mouse movements en route to specific responses on a screen, researchers glean continuous information about tentative commitments to multiple response alternatives over time. This approach yields a richness of data that can be fully explored with a variety of sophisticated analytic techniques, but these approaches are relatively underutilized and can be difficult to adopt. Here we describe several techniques for researchers to examine the onset and timing of evolving decision processes; test the degree of response competition at different time points; assess trajectory complexity with spatial disorder analyses; identify qualitatively distinct psychological processes during response generation; and finally to distill unique and meaningful components from mouse-tracking data for subsequent analysis. With this guide, we hope researchers can address novel hypotheses otherwise inaccessible with more traditional methods. analytic techniques that capitalize on the richness of data provided by a mouse-tracking approach. First, to provide a larger framework conducive for understanding, we discuss the basic paradigm, the theoretical principles underlying the method, and provide examples of what novel hypotheses this technique has already been used to test. [AQ: 1][AQ: 2][AQ: 3] We then provide step-by-step instructions for researchers to analyze the high-resolution tempo-ral data provided by mouse-tracking with several techniques, and how these data might be analyzed to address unique questions that would otherwise be unanswerable with more traditional measures. Namely, we focus on (a) time course analyses of mouse-trajectory coordinates, useful in examin-ing how various factors exert influence on or are integrated into the evolving decision process over time; (b) examination of velocity and accelera-tion, which can index the degree of response competition at different time points; (c) assess-ment of spatial disorder in trajectories, indicative of complexity and unpredictability associated with response dynamics; (d) the identification of smooth versus abrupt response competition, which can yield important insights into the pres-ence of more dynamic versus more discrete-like cognitive processes; and finally, (e) principle com-ponents analysis (PCA), which can distill unique and meaningful components from the mouse-tracking data for subsequent analysis. Because of our own work with mouse-tracking, many of the examples will be drawn from the person percep-tion and social categorization literature, but we stress that the methodology is readily applicable to diverse domains","bibtype":"article","author":"Hehman, Eric and Stolier, Ryan M and Freeman, Jonathan B and Freeman, Jon","journal":"Group Processes & Intergroup Relations","bibtex":"@article{\n title = {Advanced mouse-tracking analytic techniques for enhancing psychological science Basic Paradigm},\n type = {article},\n identifiers = {[object Object]},\n keywords = {computer mouse-tracking,face perception,impression formation,person perception},\n pages = {1-18},\n id = {8f7c6176-273a-3fd1-8afe-6ec5087b6955},\n created = {2017-09-01T15:53:50.831Z},\n file_attached = {true},\n profile_id = {80da7853-f7b7-36a9-8e4c-d7ddb2d9e538},\n group_id = {a2333ea3-15a4-3d40-8d36-f0d9590ca926},\n last_modified = {2017-09-01T15:53:50.928Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n abstract = {\" The best laid plans of mice and men often go awry. \" (Burns, 1785) And often, going awry is psychologically mean-ingful. Recent advances in psychological science have shown that motion trajectories reflect underlying cognitive processes. In the current article, we discuss how analysis of computer mouse-trajectories and their temporal dynamics can provide powerful insight into these processes. Our goal is to describe how researchers might incorporate mouse-tracking into their psycholog-ical toolbox such that they can address novel hypotheses within their areas of research. We pri-marily focus on recently developed advanced Abstract Computer mouse-tracking is a relatively recently developed behavioral methodology that can contribute unique insight into a wide variety of psychological phenomena. By recording mouse movements en route to specific responses on a screen, researchers glean continuous information about tentative commitments to multiple response alternatives over time. This approach yields a richness of data that can be fully explored with a variety of sophisticated analytic techniques, but these approaches are relatively underutilized and can be difficult to adopt. Here we describe several techniques for researchers to examine the onset and timing of evolving decision processes; test the degree of response competition at different time points; assess trajectory complexity with spatial disorder analyses; identify qualitatively distinct psychological processes during response generation; and finally to distill unique and meaningful components from mouse-tracking data for subsequent analysis. With this guide, we hope researchers can address novel hypotheses otherwise inaccessible with more traditional methods. analytic techniques that capitalize on the richness of data provided by a mouse-tracking approach. First, to provide a larger framework conducive for understanding, we discuss the basic paradigm, the theoretical principles underlying the method, and provide examples of what novel hypotheses this technique has already been used to test. [AQ: 1][AQ: 2][AQ: 3] We then provide step-by-step instructions for researchers to analyze the high-resolution tempo-ral data provided by mouse-tracking with several techniques, and how these data might be analyzed to address unique questions that would otherwise be unanswerable with more traditional measures. Namely, we focus on (a) time course analyses of mouse-trajectory coordinates, useful in examin-ing how various factors exert influence on or are integrated into the evolving decision process over time; (b) examination of velocity and accelera-tion, which can index the degree of response competition at different time points; (c) assess-ment of spatial disorder in trajectories, indicative of complexity and unpredictability associated with response dynamics; (d) the identification of smooth versus abrupt response competition, which can yield important insights into the pres-ence of more dynamic versus more discrete-like cognitive processes; and finally, (e) principle com-ponents analysis (PCA), which can distill unique and meaningful components from the mouse-tracking data for subsequent analysis. Because of our own work with mouse-tracking, many of the examples will be drawn from the person percep-tion and social categorization literature, but we stress that the methodology is readily applicable to diverse domains},\n bibtype = {article},\n author = {Hehman, Eric and Stolier, Ryan M and Freeman, Jonathan B and Freeman, Jon},\n journal = {Group Processes & Intergroup Relations}\n}","author_short":["Hehman, E.","Stolier, R., M.","Freeman, J., B.","Freeman, J."],"urls":{"Paper":"http://bibbase.org/service/mendeley/80da7853-f7b7-36a9-8e4c-d7ddb2d9e538/file/6f6393fe-3e87-fedd-4b25-4ed6296530b4/Advanced_mouse-tracking_analytic_techniques_for_enhancing_psychological_science_Basic_Paradigm.pdf.pdf"},"bibbaseid":"hehman-stolier-freeman-freeman-advancedmousetrackinganalytictechniquesforenhancingpsychologicalsciencebasicparadigm","role":"author","keyword":["computer mouse-tracking","face perception","impression formation","person perception"],"downloads":0},"search_terms":["advanced","mouse","tracking","analytic","techniques","enhancing","psychological","science","basic","paradigm","hehman","stolier","freeman","freeman"],"keywords":["computer mouse-tracking","face perception","impression formation","person perception"],"authorIDs":[]}