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Behavior Research Methods

Uri Korisky, Rony Hirschhorn, Liad Mudrik
Continuous flash suppression (CFS) is a popular method for suppressing visual stimuli from awareness for relatively long periods. Thus far, this method has only been used for suppressing two-dimensional images presented on screen. We present a novel variant of CFS, termed "real-life" CFS, in which a portion of the actual immediate surroundings of an observer-including three-dimensional, real-life objects-can be rendered unconscious. Our method uses augmented reality goggles to present subjects with CFS masks to the dominant eye, leaving the nondominant eye exposed to the real world...
November 14, 2018: Behavior Research Methods
Nicolas Dirix, Marc Brysbaert, Wouter Duyck
In the present study we assessed the extent to which different word recognition time measures converge, using large databases of lexical decision times and eyetracking measures. We observed a low proportion of shared variance between these measures, which limits the validity of lexical decision times to real-life reading. We further investigated and compared the role of word frequency and length, two important predictors of word-processing latencies in these paradigms, and found that they influenced the measures to different extents...
November 12, 2018: Behavior Research Methods
Simon G Hosking, Christopher J Best, Dawei Jia, Peter Ross, Patrick Watkinson
The processes underlying team effectiveness can be understood by analyzing the temporal dynamics of team communication sequences. The results of such analyses have shown that the complexity of team communication is associated with team performance on task-related variables, and hence communication complexity statistics have been proposed for use as measures for real-time feedback on team performance. In two analyses of historical team communication sequences, we found that filtering via use of a transmission-duration threshold and voice activity detection algorithm resulted in significant changes in complexity relative to not filtering the data or using a transmission-duration filter alone...
November 12, 2018: Behavior Research Methods
Mikhail Startsev, Ioannis Agtzidis, Michael Dorr
Deep learning approaches have achieved breakthrough performance in various domains. However, the segmentation of raw eye-movement data into discrete events is still done predominantly either by hand or by algorithms that use hand-picked parameters and thresholds. We propose and make publicly available a small 1D-CNN in conjunction with a bidirectional long short-term memory network that classifies gaze samples as fixations, saccades, smooth pursuit, or noise, simultaneously assigning labels in windows of up to 1 s...
November 8, 2018: Behavior Research Methods
Sunyoung Park, S Natasha Beretvas
Primary studies increasingly report information that can be used to provide multiple effect sizes. Of interest in this study, primary studies might compare a treatment and a control group on multiple related outcomes that result in multiple dependent effect sizes to be synthesized. There are a number of ways to handle the resulting within-study "multiple-outcome" dependency. The present study focuses on use of the multilevel meta-analysis model (Van den Noortgate, López-López, Marín-Martínez, & Sánchez-Meca, 2013) and robust variance estimation (Hedges, Tipton, & Johnson, 2010) for handling this dependency, as well as for estimating outcome-specific mean effect sizes...
November 7, 2018: Behavior Research Methods
Se-Kang Kim, Craig L Frisby
According to Stevens's classification of measurement, continuous data can be either ratio or interval scale data. The relationship between two continuous variables is assumed to be linear and is estimated with the Pearson correlation coefficient, which assumes normality between the variables. If researchers use conventional statistics (t test or analysis of variance) or factor analysis of correlation matrices to study gender or race differences, the data are assumed to be continuous and normally distributed...
November 7, 2018: Behavior Research Methods
Nikolaos Batalas, Vassilis-Javed Khan, Minita Franzen, Panos Markopoulos, Marije Aan Het Rot
Ambulatory assessment (AA) is a research method that aims to collect longitudinal biopsychosocial data in groups of individuals. AA studies are commonly conducted via mobile devices such as smartphones. Researchers tend to communicate their AA protocols to the community in natural language by describing step-by-step procedures operating on a set of materials. However, natural language requires effort to transcribe onto and from the software systems used for data collection, and may be ambiguous, thereby making it harder to reproduce a study...
November 7, 2018: Behavior Research Methods
Lieke Voncken, Casper J Albers, Marieke E Timmerman
Test publishers usually provide confidence intervals (CIs) for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored. To express uncertainty due to norming, we propose a flexible method that is applicable in continuous norming and allows for a variety of score distributions, using Generalized Additive Models for Location, Scale, and Shape (GAMLSS; Rigby & Stasinopoulos, 2005). We assessed the performance of this method in a simulation study, by examining the quality of the resulting CIs...
November 6, 2018: Behavior Research Methods
Laura Kolbe, Terrence D Jorgensen
Restricted factor analysis (RFA) is a powerful method to test for uniform differential item functioning (DIF), but it may require empirically selecting anchor items to prevent inflated Type I error rates. We conducted a simulation study to compare two empirical anchor-selection strategies: a one-step rank-based strategy and an iterative selection procedure. Unlike the iterative procedure, the rank-based strategy had a low risk and degree of contamination within the empirically selected anchor set, even with small samples...
November 6, 2018: Behavior Research Methods
Anja Pahor, Trevor Stavropoulos, Susanne M Jaeggi, Aaron R Seitz
Many cognitive tasks have been adapted for tablet-based testing, but tests to assess nonverbal reasoning ability, as measured by matrix-type problems that are suited to repeated testing, have yet to be adapted for and validated on mobile platforms. Drawing on previous research, we developed the University of California Matrix Reasoning Task (UCMRT)-a short, user-friendly measure of abstract problem solving with three alternate forms that works on tablets and other mobile devices and that is targeted at a high-ability population frequently used in the literature (i...
October 26, 2018: Behavior Research Methods
Mirjam Moerbeek
Researchers often have informative hypotheses in mind when comparing means across treatment groups, such as H1  : μA  < μB  < μC and H2  : μB  < μA  < μC , and want to compare these hypotheses to each other directly. This can be done by means of Bayesian inference. This article discusses the disadvantages of the frequentist approach to null hypothesis testing and the advantages of the Bayesian approach. It demonstrates how to use the Bayesian approach to hypothesis testing in the setting of cluster-randomized trials...
October 22, 2018: Behavior Research Methods
Maxwell R Hong, Ying Cheng
Self-report data are common in psychological and survey research. Unfortunately, many of these samples are plagued with careless responses, due to unmotivated participants. The purpose of this study was to propose and evaluate a robust estimation method to detect careless or unmotivated responders, while leveraging item response theory (IRT) person-fit statistics. First, we outlined a general framework for robust estimation specific for IRT models. Subsequently, we conducted a simulation study covering multiple conditions in order to evaluate the performance of the proposed method...
October 22, 2018: Behavior Research Methods
Christopher Sears, Leanne Quigley, Amanda Fernandez, Kristin Newman, Keith Dobson
Cognitive theories of anxiety disorders and depression posit that attentional biases play a role in the development, maintenance, and recurrence of these disorders. Several paradigms have been used to examine attentional biases in anxiety and depression, but information on the reliability of different attentional bias indices is limited. In this study we examined the internal consistency and 6-month test-retest reliability of attentional bias indices derived from a free-viewing eye-tracking paradigm. Participants completed two versions of an eye-tracking task-one that used naturalistic images as stimuli, and one that used face images...
October 22, 2018: Behavior Research Methods
Ignace T C Hooge, Gijs A Holleman, Nina C Haukes, Roy S Hessels
Most modern video eye trackers deliver binocular data. Many researchers take the average of the left and right eye signals (the version signal) to decrease the variable error (precision) up to a factor of [Formula: see text]. What happens to the systematic error (accuracy) if the left and right eye signals are averaged? To determine the systematic error, we conducted a calibration validation in two experiments (n= 79 and n = 64). The systematic error was computed for the left eye, right eye, and version signals separately...
October 22, 2018: Behavior Research Methods
G Lafay, M Rossignol, N Misdariis, M Lagrange, J-F Petiot
This paper introduces a new experimental protocol for studying mental representations of urban soundscapes through a simulation process. Subjects are asked to create a full soundscape by means of a dedicated software tool, coupled with a structured sound data set. This paradigm is used to characterize urban sound environment representations by analyzing the sound classes that were used to simulate the auditory scenes. A rating experiment of the soundscape pleasantness using a seven-point bipolar semantic scale is conducted to further refine the analysis of the simulated urban acoustic scenes...
October 17, 2018: Behavior Research Methods
Raimondas Zemblys, Diederick C Niehorster, Kenneth Holmqvist
Existing event detection algorithms for eye-movement data almost exclusively rely on thresholding one or more hand-crafted signal features, each computed from the stream of raw gaze data. Moreover, this thresholding is largely left for the end user. Here we present and develop gazeNet, a new framework for creating event detectors that do not require hand-crafted signal features or signal thresholding. It employs an end-to-end deep learning approach, which takes raw eye-tracking data as input and classifies it into fixations, saccades and post-saccadic oscillations...
October 17, 2018: Behavior Research Methods
Janice Attard-Johnson, Caoilte Ó Ciardha, Markus Bindemann
Changes in eye-pupil size index a range of cognitive processes. However, variations in the protocols used to analyze such data exist in the psychological literature. This raises the question of whether different approaches to pupillary response data influence the outcome of the analysis. To address this question, four methods of analysis were compared, using pupillary responses to sexually appetitive visual content as example data. These methods comprised analysis of the unadjusted (raw) pupillary response data, z-scored data, percentage-change data, and data transformed by a prestimulus baseline correction...
October 15, 2018: Behavior Research Methods
Julien Mayor, Nivedita Mani
The MacArthur-Bates Communicative Development Inventories (CDIs) are among the most widely used evaluation tools for early language development. CDIs are filled in by the parents or caregivers of young children by indicating which of a prespecified list of words and/or sentences their child understands and/or produces. Despite the success of these instruments, their administration is time-consuming and can be of limited use in clinical settings, multilingual environments, or when parents possess low literacy skills...
October 10, 2018: Behavior Research Methods
Amanda Kay Montoya
Moderation hypotheses appear in every area of psychological science, but the methods for testing and probing moderation in two-instance repeated measures designs are incomplete. This article begins with a short overview of testing and probing interactions in between-participant designs. Next I review the methods outlined in Judd, McClelland, and Smith (Psychological Methods 1; 366-378, 1996) and Judd, Kenny, and McClelland (Psychological Methods 6; 115-134, 2001) for estimating and conducting inference on an interaction between a repeated measures factor and a single between-participant moderator using linear regression...
October 10, 2018: Behavior Research Methods
Seth Frey, Karsten Donnay, Dirk Helbing, Robert W Sumner, Maarten W Bos
Even though human behavior is largely driven by real-time feedback from others, this social complexity is underrepresented in psychological theory, largely because it is so difficult to isolate. In this work, we performed a quasi-experimental analysis of hundreds of millions of chat room messages between young people. This allowed us to reconstruct how-and on what timeline-the valence of one message affects the valence of subsequent messages by others. For the highly emotionally valenced chat messages that we focused on, we found that these messages elicited a general increase of 0...
October 10, 2018: Behavior Research Methods
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