Showing papers in "Behavior Research Methods in 2009"
TL;DR: In the new version, procedures to analyze the power of tests based on single-sample tetrachoric correlations, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression are added.
Abstract: G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
20,778 citations
TL;DR: The familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models are described and macros for SPSS and SAS are introduced to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression.
Abstract: Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.
2,204 citations
TL;DR: The size of the corpus, the language register on which the corpus is based, and the definition of the frequency measure were investigated, finding that lemma frequencies are not superior to word form frequencies in English and that a measure of contextual diversity is better than a measure based on raw frequency of occurrence.
Abstract: Word frequency is the most important variable in research on word processing and memory. Yet, the main criterion for selecting word frequency norms has been the availability of the measure, rather than its quality. As a result, much research is still based on the old Kucera and Francis frequency norms. By using the lexical decision times of recently published megastudies, we show how bad this measure is and what must be done to improve it. In particular, we investigated the size of the corpus, the language register on which the corpus is based, and the definition of the frequency measure. We observed that corpus size is of practical importance for small sizes (depending on the frequency of the word), but not for sizes above 16–30 million words. As for the language register, we found that frequencies based on television and film subtitles are better than frequencies based on written sources, certainly for the monosyllabic and bisyllabic words used in psycholinguistic research. Finally, we found that lemma frequencies are not superior to word form frequencies in English and that a measure of contextual diversity is better than a measure based on raw frequency of occurrence. Part of the superiority of the latter is due to the words that are frequently used as names. Assembling a new frequency norm on the basis of these considerations turned out to predict word processing times much better than did the existing norms (including Kucera & Francis and Celex). The new SUBTL frequency norms from the SUBTLEXUS corpus are freely available for research purposes from http://brm.psychonomic-journals.org/content/supplemental, as well as from the University of Ghent and Lexique Web sites.
2,106 citations
TL;DR: A method for automatically detecting syllable nuclei in order to measure speech rate without the need for a transcription is described and it is concluded that a syllable count measured in this automatic fashion suffices to reliably assess and compare speech rates between participants and tasks.
Abstract: In this article, we describe a method for automatically detecting syllable nuclei in order to measure speech rate without the need for a transcription. A script written in the software program Praat (Boersma & Weenink, 2007) detects syllables in running speech. Peaks in intensity (dB) that are preceded and followed by dips in intensity are considered to be potential syllable nuclei. The script subsequently discards peaks that are not voiced. Testing the resulting syllable counts of this script on two corpora of spoken Dutch, we obtained high correlations between speech rate calculated from human syllable counts and speech rate calculated from automatically determined syllable counts. We conclude that a syllable count measured in this automatic fashion suffices to reliably assess and compare speech rates between participants and tasks.
500 citations
TL;DR: A coding system combined with an annotation tool for the analysis of gestural behavior and the combination of the NEUROGES coding system and the annotation tool ELAN creates an effective tool for empirical research on Gestural behavior.
Abstract: We present a coding system combined with an annotation tool for the analysis of gestural behavior. The NEUROGES coding system consists of three modules that progress from gesture kinetics to gesture function. Grounded on empirical neuropsychological and psychological studies, the theoretical assumption behind NEUROGES is that its main kinetic and functional movement categories are differentially associated with specific cognitive, emotional, and interactive functions. ELAN is a free, multimodal annotation tool for digital audio and video media. It supports multileveled transcription and complies with such standards as XML and Unicode. ELAN allows gesture categories to be stored with associated vocabularies that are reusable by means of template files. The combination of the NEUROGES coding system and the annotation tool ELAN creates an effective tool for empirical research on gestural behavior.
455 citations
TL;DR: The BAWL-R is intended to help researchers create stimulus material for a wide range of experiments dealing with the affective processing of German verbal material, and is the first list that not only contains a large set of psycholinguistic indexes known to influence word processing, but also features ratings regarding emotional arousal.
Abstract: The study presented here provides researchers with a revised list of affective German words, the Berlin Affective Word List Reloaded (BAWL-R). This work is an extension of the previously published BAWL (Vo, Jacobs, & Conrad, 2006), which has enabled researchers to investigate affective word processing with highly controlled stimulus material. The lack of arousal ratings, however, necessitated a revised version of the BAWL. We therefore present the BAWL-R, which is the first list that not only contains a large set of psycholinguistic indexes known to influence word processing, but also features ratings regarding emotional arousal, in addition to emotional valence and imageability. The BAWL-R is intended to help researchers create stimulus material for a wide range of experiments dealing with the affective processing of German verbal material.
430 citations
TL;DR: Effect-size measures offer a means to evaluate both component paths and the overall mediated effect in mediation models and indicate acceptable bias across varying parameter and sample-size combinations.
Abstract: R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.
275 citations
TL;DR: A program for implementing a computerized version of the NASA TLX, a popular technique for measuring subjective mental workload, which relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales.
Abstract: The NASA Task Load Index (TLX) is a popular technique for measuring subjective mental workload. It relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales: mental demand, physical demand, temporal demand, performance, effort, and frustration level. A program for implementing a computerized version of the NASA TLX is described. The software version assists in simplifying collection, postprocessing, and storage of raw data. The program collects raw data from the subject and calculates the weighted (or unweighted) workload score, which is output to a text file. The program can also be tailored to a specific experiment using a simple input text file, if desired. The program was designed in Visual Studio 2005 and is capable of running on a Pocket PC with Windows CE or on a PC with Windows 2000 or higher. The NASA TLX program is available for free download.
199 citations
TL;DR: In the present article, 11 methods for constructing the confidence intervals (CIs) of the standardized indirect effects were evaluated via a computer simulation and consistently showed that the percentile bootstrap, the bias-correctedbootstrap, and the likelihood-based approaches had the best coverage probability.
Abstract: Mediation models are often used as a means to explain the psychological mechanisms between an independent and a dependent variable in the behavioral and social sciences. A major limitation of the unstandardized indirect effect calculated from raw scores is that it cannot be interpreted as an effect-size measure. In contrast, the standardized indirect effect calculated from standardized scores can be a good candidate as a measure of effect size because it is scale invariant. In the present article, 11 methods for constructing the confidence intervals (CIs) of the standardized indirect effects were evaluated via a computer simulation. These included six Wald CIs, three bootstrap CIs, one likelihood-based CI, and the PRODCLIN CI. The results consistently showed that the percentile bootstrap, the bias-corrected bootstrap, and the likelihood-based approaches had the best coverage probability. Mplus, LISREL, and Mx syntax were included to facilitate the use of these preferred methods in applied settings. Future issues on the use of the standardized indirect effects are discussed.
198 citations
TL;DR: Although there already exists a number of sets of word and object norms, this work provides the first set to categorize words describing object properties along the dimensions of the five perceptual modalities, and contains estimates of modality exclusivity.
Abstract: Recent work has shown that people routinely use perceptual information during language comprehension and conceptual processing, from single-word recognition to modality-switching costs in property verification. In investigating such links between perceptual and conceptual representations, the use of modality-specific stimuli plays a central role. To aid researchers working in this area, we provide a set of norms for 423 adjectives, each describing an object property, with mean ratings of how strongly that property is experienced through each of five perceptual modalities (visual, haptic, auditory, olfactory, and gustatory). The data set also contains estimates of modality exclusivity—that is, a measure of the extent to which a particular property may be considered unimodal (i.e., perceived through one sense alone). Although there already exists a number of sets of word and object norms, we provide the first set to categorize words describing object properties along the dimensions of the five perceptual modalities. We hope that the norms will be of use to researchers working at the interface between linguistic, conceptual, and perceptual systems. The modality exclusivity norms may be downloaded as supplemental materials for this article from brm.psychonomic-journals.org/ content/supplemental.
181 citations
TL;DR: CowLog, which is open-source software for recording behaviors from digital video and is easy to use and modify, comes with an additional feature, an R package called Animal, for elementary analyses of the data files.
Abstract: We have developed CowLog, which is open-source software for recording behaviors from digital video and is easy to use and modify. CowLog tracks the time code from digital video files. The program is suitable for coding any digital video, but the authors have used it in animal research. The program has two main windows: a coding window, which is a graphical user interface used for choosing video files and defining output files that also has buttons for scoring behaviors, and a video window, which displays the video used for coding. The windows can be used in separate displays. The user types the key codes for the predefined behavioral categories, and CowLog transcribes their timing from the video time code to a data file. CowLog comes with an additional feature, an R package called Animal, for elementary analyses of the data files. With the analysis package, the user can calculate the frequencies, bout durations, and total durations of the coded behaviors and produce summary plots from the data.
TL;DR: Interval estimates of the average treatment effect were examined for two specifications of the Level 1 error structure (σ2I and first-order autoregressive) and for five different methods of estimating the degrees of freedom (containment, residual, between—within, Satterthwaite, and Kenward—Roger).
Abstract: Multiple-baseline studies are prevalent in behavioral research, but questions remain about how to best analyze the resulting data. Monte Carlo methods were used to examine the utility of multilevel models for multiplebaseline data under conditions that varied in the number of participants, number of repeated observations per participant, variance in baseline levels, variance in treatment effects, and amount of autocorrelation in the Level 1 errors. Interval estimates of the average treatment effect were examined for two specifications of the Level 1 error structure (σ2I and first-order autoregressive) and for five different methods of estimating the degrees of freedom (containment, residual, between—within, Satterthwaite, and Kenward—Roger). When the Satterthwaite or Kenward—Roger method was used and an autoregressive Level 1 error structure was specified, the interval estimates of the average treatment effect were relatively accurate. Conversely, the interval estimates of the treatment effect variance were inaccurate, and the corresponding point estimates were biased.
TL;DR: This work evaluates a simple metric of pointwise mutual information and demonstrates that this metric benefits from training on extremely large amounts of data and correlates more closely with human semantic similarity ratings than do publicly available implementations of several more complex models.
Abstract: Computational models of lexical semantics, such as latent semantic analysis, can automatically generate semantic similarity measures between words from statistical redundancies in text. These measures are useful for experimental stimulus selection and for evaluating a model’s cognitive plausibility as a mechanism that people might use to organize meaning in memory. Although humans are exposed to enormous quantities of speech, practical constraints limit the amount of data that many current computational models can learn from. We follow up on previous work evaluating a simple metric of pointwise mutual information. Controlling for confounds in previous work, we demonstrate that this metric benefits from training on extremely large amounts of data and correlates more closely with human semantic similarity ratings than do publicly available implementations of several more complex models. We also present a simple tool for building simple and scalable models from large corpora quickly and efficiently.
TL;DR: Three studies in which a new virtual reality paradigm was used, in which participants had to escape from a burning underground rail station, support a hypothesis according to which (emergent) collective identity motivates solidarity with strangers.
Abstract: Virtual reality technology is argued to be suitable to the simulation study of mass evacuation behavior, because of the practical and ethical constraints in researching this field. This article describes three studies in which a new virtual reality paradigm was used, in which participants had to escape from a burning underground rail station. Study 1 was carried out in an immersion laboratory and demonstrated that collective identification in the crowd was enhanced by the (shared) threat embodied in emergency itself. In Study 2, high-identification participants were more helpful and pushed less than did low-identification participants. In Study 3, identification and group size were experimentally manipulated, and similar results were obtained. These results support a hypothesis according to which (emergent) collective identity motivates solidarity with strangers. It is concluded that the virtual reality technology developed here represents a promising start, although more can be done to embed it in a traditional psychology laboratory setting.
TL;DR: MLP, a MATLAB toolbox enabling auditory thresholds estimation via the adaptive maximum likelihood procedure proposed by David Green (1990, 1993), is presented.
Abstract: In this article, we present MLP, a MATLAB toolbox enabling auditory thresholds estimation via the adaptive maximum likelihood procedure proposed by David Green (1990, 1993). This adaptive procedure is particularly appealing for those psychologists who need to estimate thresholds with a good degree of accuracy and in a short time. Together with a description of the toolbox, the present text provides an introduction to the threshold estimation theory and a theoretical explanation of the maximum likelihood adaptive procedure. MLP comes with a graphical interface, and it is provided with several built-in, classic psychoacoustics experiments ready to use at a mouse click.
TL;DR: Multiple alternative measures of transparency are reported, using both type and token counts, and compared with estimates for other languages, to discuss the problems stemming from restricted analysis sets and the implications for psycholinguistic experimentation and computational modeling of reading and spelling.
Abstract: Orthographic transparency refers to the systematicity in the mapping between orthographic letter sequences and phonological phoneme sequences in both directions, for reading and spelling. Measures of transparency previously used in the analysis of orthographies of other languages include regularity, consistency, and entropy. However, previous reports have typically been hampered by severe restrictions, such as using only monosyllables or only word-initial phonemes. Greek is sufficiently transparent to allow complete sequential alignment between graphemes and phonemes, therefore permitting full analyses at both letter and grapheme levels, using every word in its entirety. Here, we report multiple alternative measures of transparency, using both type and token counts, and compare these with estimates for other languages. We discuss the problems stemming from restricted analysis sets and the implications for psycholinguistic experimentation and computational modeling of reading and spelling.
TL;DR: The automatic learning device for monkeys (ALDM) is a computerized test system controlled by an automatic radio frequency identification of subjects, provided ad lib inside the social group of monkeys, for voluntary self-testing on a 24-h schedule.
Abstract: Laboratory procedures used to study the cognitive functions of primates traditionally have involved removal of the subjects from their living quarters to be tested singly in a remote experimental room. This article presents an alternative research strategy favoring testing primates while they are maintained in their social group. The automatic learning device for monkeys (ALDM) is a computerized test system controlled by an automatic radio frequency identification of subjects. It is provided ad lib inside the social group of monkeys, for voluntary self-testing on a 24-h schedule. Nine baboons were tested with ALDM during a 7-month period. Experiments were performed to assess learning in motor control and abstract reasoning tasks. The results revealed high trial frequencies and excellent learning performance, even in tasks involving the highest cognitive complexities. A different study using ALDM with a group of 3 rhesus monkeys revealed social influences on learning. Beyond its interest for cognitive psychologists, ALDM is of interest for pharmacologists and cognitive neuroscientists working with nonhuman primates. ALDM also can serve as an enrichment tool for captive animals and may be used to study a variety of species other than primates.
TL;DR: Two experiments demonstrate the feasibility of collecting response latency data over the World-Wide Web using WebExp—a software package designed to run psychological experiments over the Internet and conclude that WebExp can be used to obtain reliable response time data, at least for the self-paced reading paradigm.
Abstract: Although Internet-based experiments are gaining in popularity, most studies rely on directly evaluating participants’ responses rather than response times. In the present article, we present two experiments that demonstrate the feasibility of collecting response latency data over the World-Wide Web using WebExp—a software package designed to run psychological experiments over the Internet. Experiment 1 uses WebExp to collect measurements for known time intervals (generated using keyboard repetition). The resulting measurements are found to be accurate across platforms and load conditions. In Experiment 2, we use WebExp to replicate a lab-based self-paced reading study from the psycholinguistic literature. The data of the Web-based replication correlate significantly with those of the original study and show the same main effects and interactions. We conclude that WebExp can be used to obtain reliable response time data, at least for the self-paced reading paradigm.
TL;DR: The Adaptive Visual Analog Scales is a freely available computer software package designed to be a flexible tool for the creation, administration, and automated scoring of both continuous and discrete visual analog scale formats.
Abstract: The Adaptive Visual Analog Scales is a freely available computer software package designed to be a flexible tool for the creation, administration, and automated scoring of both continuous and discrete visual analog scale formats. The continuous format is a series of individual items that are rated along a solid line and scored as a percentage of distance from one of the two anchors of the rating line. The discrete format is a series of individual items that use a specific number of ordinal choices for rating each item. This software offers separate options for the creation and use of standardized instructions, practice sessions, and rating administration, all of which can be customized by the investigator. A unique participant/patient ID is used to store scores for each item, and individual data from each administration are automatically appended to that scale’s data storage file. This software provides flexible, time-saving access for data management and/or importing data into statistical packages. This tool can be adapted so as to gather ratings for a wide range of clinical and research uses and is freely available at www.nrlc-group.net.
TL;DR: This article describes how The Observer XT was used to integrate and synchronize video, observational, tracking, and physiological data from an experiment carried out in 2001 at the Wageningen Institute of Animal Sciences of Wageneden University and Research Centre.
Abstract: The Observer was originally developed as a manual event recorder for the collection, management, analysis, and presentation of observational data in animals. Because of the flexibility of later versions, it became clear that The Observer was suitable for almost any study involving collection of observational data in both animals and humans. Furthermore, the most recent version of The Observer (The Observer XT) allows the integration and synchronization of multimodal signals from various sources, such as observational, video, tracking, and physiological data. This article describes how The Observer XT was used to integrate and synchronize video, observational, tracking, and physiological data from an experiment carried out in 2001 at the Wageningen Institute of Animal Sciences of Wageningen University and Research Centre. The integration and synchronization of these multimodal signals in The Observer XT allows the user to draw a more complete picture of the phenomena under study.
TL;DR: Reporting of both a time-based and an event-based Cohen’s κ?is recommended, due to the somewhat different information provided by each.
Abstract: Observer agreement is often regarded as the sine qua non of observational research. Cohen’s κ ?is a widely used index and is appropriate when discrete entities—such as a turn-of-talk or a demarcated time interval—are presented to pairs of observers to code. κ-like statistics and agreement matrices are also used for the timed-event sequential data produced when observers first segment and then code events detected in the stream of behavior, noting onset and offset times. Such κs are of two kinds: time-based and event-based. Available for download is a computer program (OASTES; Observer Agreement for Simulated Timed Event Sequences) that simulates the coding of observers of a stated accuracy and then computes agreement statistics for two time-based κs (with and without tolerance) and three event-based κs (one implemented in The Observer, one in INTERACT, and one in GSEQ). On the basis of simulation results presented here, and due to the somewhat different information provided by each, the reporting of both a time-based and an event-based κ?is recommended.
TL;DR: It is demonstrated how the methods instantiated within these systems can be used to make sense of the large amount of data generated by eyetracking and keystroke logging in order to inform understanding of the cognitive processes that underlie written text production.
Abstract: Writers typically spend a certain proportion of time looking back over the text that they have written. This is likely to serve a number of different functions, which are currently poorly understood. In this article, we present two systems, ScriptLog+TimeLine and EyeWrite, that adopt different and complementary approaches to exploring this activity by collecting and analyzing combined eye movement and keystroke data from writers composing extended texts. ScriptLog+TimeLine is a system that is based on an existing keystroke-logging program and uses heuristic, pattern-matching methods to identify reading episodes within eye movement data. EyeWrite is an integrated editor and analysis system that permits identification of the words that the writer fixates and their location within the developing text. We demonstrate how the methods instantiated within these systems can be used to make sense of the large amount of data generated by eyetracking and keystroke logging in order to inform understanding of the cognitive processes that underlie written text production.
TL;DR: This investigation proposes a new model of analysis for studying the effectiveness and construction of offensive basketball plays in order to identify their outcomes, thus providing coaches with an important device for improving or consolidating them.
Abstract: In the field of sports research, there is a growing need for the rigorous collection of data that provide empirical evidence about the complex reality they refer to. Although sports psychology research has advanced considerably in recent years, in both extent and quality, one area of research that remains relatively unexplored is the dynamics of the sports group and the influence of the group on its members (George & Feltz, 1995; Widmeyer, Brawley, & Carron, 1992). Key aspects in this regard include the presence of regularities that are not detectable through visual inference or traditional methods of data analysis, the lack of standard observation instruments, and, assuming priority, the need to develop powerful, computerized coding systems, all of which must form part of an approach that is suitable for natural and habitual contexts. The present study is part of a broader research project concerning ACB teams (first Spanish basketball division) and considers the interaction context before teams try to score (where this is understood as how teams create scoring opportunities) as the core aspect that links team play. This investigation proposes a new model of analysis for studying the effectiveness and construction of offensive basketball plays in order to identify their outcomes, thus providing coaches with an important device for improving or consolidating them.
TL;DR: The results, as reflected by the T-patterns detected, show that participants try to generate their own motor skills but copy some fundamental components of the instructions, and the criterion of stability in two configurations (support and axial) is the predominant category.
Abstract: The present article analyzes the diversity of motor skills related to three different kinds of instructions: descriptive, metaphoric, and kinesic, with a special emphasis on the detection of temporal patterns (T-patterns). Twelve undergraduates studying sport and physical education, but without experience in dance, were observed during 24 lessons of Body Movement, a discipline based on creative dance, mime dance, and motor skill improvisation. Using observational methodology and technology applied to movement, the aim of this article was to adapt the Observational instrument of Motor Skills (OSMOS) (Castaner, Torrents, Anguera, & Dinusova, 2008) so as to create an instrument capable of analyzing the motor skill responses generated in lessons of Body Movement and Dance. The results, as reflected by the T-patterns detected, show that (1) participants try to generate their own motor skills but copy some fundamental components of the instructions, and (2) the criterion of stability in two configurations (support and axial) is the predominant category. Sequential and coordinated locomotion also appears to be very relevant.
TL;DR: The advantages and limitations for valid inferences are discussed, a statistical technique—randomization tests—for use with multiple-baseline data, to complement visual analysis is suggested, and an extension of the SCRT-R package is provided.
Abstract: Multiple-baseline designs are an extension of the basic single-case AB phase designs, in which several of those AB designs are implemented simultaneously to different persons, behaviors, or settings, and the intervention is introduced in a staggered way to the different units. These designs are well-suited for research in the behavioral sciences. We discuss the advantages and limitations for valid inferences, and suggest a statistical technique—randomization tests—for use with multiple-baseline data, to complement visual analysis. In addition, we provide an extension of our SCRT-R package (which already contained means for conducting randomization tests on single-case phase and alternation designs), for multiple-baseline AB data.
TL;DR: This work investigated whether pairs of coders extract similar data from the same graphs (reliability), and whether the extracted data match numerical descriptions of the graph that the original author may have presented in tables or text (validity).
Abstract: Certain research tasks require extracting data points from graphs and charts Using 91 graphs that presented results from single-case designs, we investigated whether pairs of coders extract similar data from the same graphs (reliability), and whether the extracted data match numerical descriptions of the graph that the original author may have presented in tables or text (validity) Coders extracted data using the UnGraph computer program Extraction proved highly reliable over several different kinds of analyses Coders nearly always extracted identical numbers of data points, and the values they assigned to those data points were nearly identical Extraction also proved highly valid, with the means of extracted data correlating nearly perfectly with means reported in tables or text and with very few discrepancies in any single case These results suggest that researchers can use extracted data with a high degree of confidence that they are nearly identical to the original data
TL;DR: A general framework for detecting sleepiness states on the basis of prosody, articulation, and speech-quality-related speech characteristics is described, which is nonobstrusive and is free from sensor application and calibration efforts.
Abstract: This article describes a general framework for detecting sleepiness states on the basis of prosody, articulation, and speech-quality-related speech characteristics. The advantages of this automatic real-time approach are that obtaining speech data is nonobstrusive and is free from sensor application and calibration efforts. Different types of acoustic features derived from speech, speaker, and emotion recognition were employed (frame-level-based speech features). Combing these features with high-level contour descriptors, which capture the temporal information of frame-level descriptor contours, results in 45,088 features per speech sample. In general, the measurement proces follows the speech-adapted steps of pattern recognition: (1) recording speech, (2) preprocesing, (3) feature computation (using perceptual and signal-procesing-related features such as, e.g., fundamental frequency, intensity, pause patterns, formants, and cepstral coefficients), (4) dimensionality reduction, (5) clasification, and (6) evaluation. After a correlation-filter-based feature subset selection employed on the feature space in order to find most relevant features, different clasification models were trained. The best model—namely, the support-vector machine—achieved 86.1% clasification accuracy in predicting sleepines in a sleep deprivation study (two-clas problem, N 5 12; 01.00-08.00 a.m.).
TL;DR: This work provides instructions and computer code for three methods for estimating the parameters of the linear ballistic accumulator (LBA), a new and computationally tractable model of decisions between two or more choices.
Abstract: Cognitive models of the decision process provide greater insight into response time and accuracy than do standard ANOVA techniques. However, such models can be mathematically and computationally difficult to apply. We provide instructions and computer code for three methods for estimating the parameters of the linear ballistic accumulator (LBA), a new and computationally tractable model of decisions between two or more choices. These methods—a Microsoft Excel worksheet, scripts for the statistical program R, and code for implementation of the LBA into the Bayesian sampling software WinBUGS—vary in their flexibility and user accessibility. We also provide scripts in R that produce a graphical summary of the data and model predictions. In a simulation study, we explored the effect of sample size on parameter recovery for each method. The materials discussed in this article may be downloaded as a supplement from http://brm.psychonomic-journals.org/content/supplemental.
TL;DR: A Black Box ToolKit is used to measure the variability in timing characteristics of hardware used commonly in psychological research, and has millisecond-accurate presentation and response timing improved, and will they ever be available in commodity computers and peripherals?
Abstract: Since the publication of Plant, Hammond, and Turner (2004), which highlighted a pressing need for researchers to pay more attention to sources of error in computer-based experiments, the landscape has undoubtedly changed, but not necessarily for the better. Readily available hardware has improved in terms of raw speed; multicore processors abound; graphics cards now have hundreds of megabytes of RAM; main memory is measured in gigabytes; drive space is measured in terabytes; ever larger thin film transistor displays capable of single-digit response times, together with newer Digital Light Processing multimedia projectors, enable much greater graphic complexity; and new 64-bit operating systems, such as Microsoft Vista, are now commonplace. However, have millisecond-accurate presentation and response timing improved, and will they ever be available in commodity computers and peripherals? In the present article, we used a Black Box ToolKit to measure the variability in timing characteristics of hardware used commonly in psychological research.
TL;DR: The maze task is an online measure of sentence processing time that provides an alternative to the standard moving window version of self-paced reading and is sensitive to word frequency effects, producing estimates well in excess of those found with eyetracking.
Abstract: The maze task is an online measure of sentence processing time that provides an alternative to the standard moving window version of self-paced reading. Rather than each word of the sentence being presented in succession, two words are presented at the same time, and the participant must choose which word is a grammatical continuation of the sentence. This procedure forces the reader into an incremental mode of processing in which each word must be fully integrated with the preceding context before the next word can be considered. Previous research with this technique has not considered whether it is sufficiently sensitive to syntactic complexity effects or to garden path effects. Four experiments are reported demonstrating that reliable differences in processing time for subject relatives and object relatives can be obtained, and that this technique generates garden path effects that correspond closely with the data from eyetracking experiments, but without the spillover effects that are sometimes obtained with eyetracking. It is also shown that the task is sensitive to word frequency effects, producing estimates well in excess of those found with eyetracking.