Behavior Research Methods

Publisher: Psychonomic Society, Springer Verlag

Journal description

Current impact factor: 2.12

Impact Factor Rankings

Additional details

5-year impact 3.90
Cited half-life 6.80
Immediacy index 0.23
Eigenfactor 0.02
Article influence 1.71
Other titles Behavior research methods (Online), Behavior research methods
ISSN 1554-3528
OCLC 57493288
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

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  • Classification
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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Houses have often been used as comparison stimuli in face-processing studies because of the many attributes they share with faces (e.g., distinct members of a basic category, consistent internal features, mono-orientation, and relative familiarity). Despite this, no large, well-controlled databases of photographs of houses that have been developed for research use currently exist. To address this gap, we photographed 100 houses and carefully edited these images. We then asked 41 undergraduate students (18 to 31 years of age) to rate each house on three dimensions: typicality, likeability, and face-likeness. The ratings had a high degree of face validity, and analyses revealed a significant positive correlation between typicality and likeability. We anticipate that this stimulus set (i.e., the DalHouses) and the associated ratings will prove useful to face-processing researchers by minimizing the effort required to acquire stimuli and allowing for easier replication and extension of studies. The photographs of all 100 houses and their ratings data can be obtained at .
    Behavior Research Methods 01/2016; DOI:10.3758/s13428-015-0561-8
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    ABSTRACT: The sensorimotor synchronization paradigm is used when studying the coordination of rhythmic motor responses with a pacing stimulus and is an important paradigm in the study of human timing and time perception. Two measures of performance frequently calculated using sensorimotor synchronization data are the average offset and variability of the stimulus-to-response asynchronies-the offsets between the stimuli and the motor responses. Here it is shown that assuming that asynchronies are normally distributed when estimating these measures can result in considerable underestimation of both the average offset and variability. This is due to a tendency for the distribution of the asynchronies to be bimodal and left skewed when the interstimulus interval is longer than 2 s. It is argued that (1) this asymmetry is the result of the distribution of the asynchronies being a mixture of two types of responses-predictive and reactive-and (2) the main interest in a sensorimotor synchronization study is the predictive responses. A Bayesian hierarchical modeling approach is proposed in which sensorimotor synchronization data are modeled as coming from a right-censored normal distribution that effectively separates the predictive responses from the reactive responses. Evaluation using both simulated data and experimental data from a study by Repp and Doggett (2007) showed that the proposed approach produces more precise estimates of the average offset and variability, with considerably less underestimation.
    Behavior Research Methods 05/2015; DOI:10.3758/s13428-015-0591-2
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    ABSTRACT: The intelligent tutoring system (ITS) BRCA Gist is a Web-based tutor developed using the Shareable Knowledge Objects (SKO) platform that uses latent semantic analysis to engage women in natural-language dialogues to teach about breast cancer risk. BRCA Gist appears to be the first ITS designed to assist patients' health decision making. Two studies provide fine-grained analyses of the verbal interactions between BRCA Gist and women responding to five questions pertaining to breast cancer and genetic risk. We examined how "gist explanations" generated by participants during natural-language dialogues related to outcomes. Using reliable rubrics, scripts of the participants' verbal interactions with BRCA Gist were rated for content and for the appropriateness of the tutor's responses. Human researchers' scores for the content covered by the participants were strongly correlated with the coverage scores generated by BRCA Gist, indicating that BRCA Gist accurately assesses the extent to which people respond appropriately. In Study 1, participants' performance during the dialogues was consistently associated with learning outcomes about breast cancer risk. Study 2 was a field study with a more diverse population. Participants with an undergraduate degree or less education who were randomly assigned to BRCA Gist scored higher on tests of knowledge than those assigned to the National Cancer Institute website or than a control group. We replicated findings that the more expected content that participants included in their gist explanations, the better they performed on outcome measures. As fuzzy-trace theory suggests, encouraging people to develop and elaborate upon gist explanations appears to improve learning, comprehension, and decision making.
    Behavior Research Methods 04/2015; DOI:10.3758/s13428-015-0592-1
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    ABSTRACT: An asymmetric one-mode data matrix has rows and columns that correspond to the same set of objects. However, the roles of the objects frequently differ for the rows and the columns. For example, in a visual alphabetic confusion matrix from an experimental psychology study, both the rows and columns pertain to letters of the alphabet. Yet the rows correspond to the presented stimulus letter, whereas the columns refer to the letter provided as the response. Other examples abound in psychology, including applications related to interpersonal interactions (friendship, trust, information sharing) in social and developmental psychology, brand switching in consumer psychology, journal citation analysis in any discipline (including quantitative psychology), and free association tasks in any subarea of psychology. When seeking to establish a partition of the objects in such applications, it is overly restrictive to require the partitions of the row and column objects to be identical, or even the numbers of clusters for the row and column objects to be the same. This suggests the need for a biclustering approach that simultaneously establishes separate partitions of the row and column objects. We present and compare several approaches for the biclustering of one-mode matrices using data sets from the empirical literature. A suite of MATLAB m-files for implementing the procedures is provided as a Web supplement with this article.
    Behavior Research Methods 04/2015; DOI:10.3758/s13428-015-0587-y
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    ABSTRACT: Researchers can use the coefficient of variation (CV), Gini coefficient, standard deviation (SD), Theil index, or relative mean deviation (RMD) to measure organizational disparity. Because these five measures have different properties, however, using them interchangeably may lead to inconsistent findings. Using simulated team pay data, we conducted two simulation studies to examine the similarities and potential differences among these measures. The results showed that CV, Gini, Theil, and RMD were strongly related in most circumstances and that interchanging them had little impact on their relations with outcome variables. Differences were observed, however, when interchanging any of these four measures (CV/Gini/Theil/RMD) with SD, especially when samples were characterized by a seriously skewed distribution, a wide pay gap, and a high sample disparity. Given that SD does not meet some of the properties of disparity, and that it may underestimate correlations between disparity and outcome variables, we suggest that researchers use CV, Gini, Theil, or RMD, rather than SD, to assess organizational disparity.
    Behavior Research Methods 04/2015; DOI:10.3758/s13428-015-0585-0
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    ABSTRACT: As commercial technology moves further into wearable technologies, cognitive and psychological scientists can capitalize on these devices to facilitate naturalistic research designs while still maintaining strong experimental control. One such wearable technology is Google Glass (Google, Inc.: ), which can present wearers with audio and visual stimuli while tracking a host of multimodal data. In this article, we introduce PsyGlass, a framework for incorporating Google Glass into experimental work that is freely available for download and community improvement over time ( ). As a proof of concept, we use this framework to investigate dual-task pressures on naturalistic interaction. The preliminary study demonstrates how designs from classic experimental psychology may be integrated in naturalistic interactive designs with emerging technologies. We close with a series of recommendations for using PsyGlass and a discussion of how wearable technology more broadly may contribute to new or adapted naturalistic research designs.
    Behavior Research Methods 04/2015; DOI:10.3758/s13428-015-0586-z
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    ABSTRACT: The analysis of vocal expression is a critical endeavor for psychological and clinical sciences and is an increasingly popular application for computer-human interfaces. Despite this, and despite advances in the efficiency, affordability, and sophistication of vocal analytic technologies, there is considerable variability across studies regarding what aspects of vocal expression are studied. Vocal signals can be quantified in a myriad of ways, and their underlying structure, at least with respect to "macroscopic" measures from extended speech, is presently unclear. To address this issue, we evaluated the psychometric properties-notably, the structural and construct validity-of a systematically defined set of global vocal features. Our analytic strategy focused on (a) identifying redundant variables among this set, (b) employing principal components analysis (PCA) to identify nonoverlapping domains of vocal expression, (c) examining the degrees to which the vocal variables are modulated as a function of changes in speech task, and (d) evaluating the relationship between the vocal variables and cognitive (i.e., verbal fluency) and clinical (i.e., depression, anxiety, and hostility) variables. Spontaneous speech samples from 11 independent studies of young adults (>60 s in length), employing one of three different speaking tasks, were examined (N = 1,350). Confounding variables (i.e., sex, ethnicity) were statistically controlled for. The PCA identified six distinct domains of vocal expression. Collectively, vocal expression (defined in terms of these domains) was modulated as a function of speech task and was related to the cognitive and clinical variables. These findings provide empirically grounded implications for the study of vocal expression in psychological and clinical sciences.
    Behavior Research Methods 04/2015; DOI:10.3758/s13428-015-0584-1
  • Behavior Research Methods 01/2015;
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    ABSTRACT: Van Hooft and Born (Journal of Applied Psychology 97:301-316, 2012) presented data challenging both the correctness of a congruence model of faking on personality test items and the relative merit (i.e., effect size) of response latencies for identifying fakers. We suggest that their analysis of response times was suboptimal, and that it followed neither from a congruence model of faking nor from published protocols on appropriately filtering the noise in personality test item answering times. Using new data and following recommended analytic procedures, we confirmed the relative utility of response times for identifying personality test fakers, and our obtained results, again, reinforce a congruence model of faking.
    Behavior Research Methods 11/2014; DOI:10.3758/s13428-014-0524-5
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    ABSTRACT: Since the work of Taft and Forster (1976), a growing literature has examined how English compound words are recognized and organized in the mental lexicon. Much of this research has focused on whether compound words are decomposed during recognition by manipulating the word frequencies of their lexemes. However, many variables may impact morphological processing, including relational semantic variables such as semantic transparency, as well as additional form-related and semantic variables. In the present study, ratings were collected on 629 English compound words for six variables [familiarity, age of acquisition (AoA), semantic transparency, lexeme meaning dominance (LMD), imageability, and sensory experience ratings (SER)]. All of the compound words selected for this study are contained within the English Lexicon Project (Balota et al., 2007), which made it possible to use a regression approach to examine the predictive power of these variables for lexical decision and word naming performance. Analyses indicated that familiarity, AoA, imageability, and SER were all significant predictors of both lexical decision and word naming performance when they were added separately to a model containing the length and frequency of the compounds, as well as the lexeme frequencies. In addition, rated semantic transparency also predicted lexical decision performance. The database of English compound words should be beneficial to word recognition researchers who are interested in selecting items for experiments on compound words, and it will also allow researchers to conduct further analyses using the available data combined with word recognition times included in the English Lexicon Project.
    Behavior Research Methods 11/2014; DOI:10.3758/s13428-014-0523-6