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Journal of the Experimental Analysis of Behavior

Manuel Villarreal, Carlos Velázquez, José L Baroja, Alejandro Segura, Arturo Bouzas, Michael D Lee
We demonstrate the usefulness of Bayesian methods in developing, evaluating, and using psychological models in the experimental analysis of behavior. We do this through a case study, involving new experimental data that measure the response count and time allocation behavior in pigeons under concurrent random-ratio random-interval schedules of reinforcement. To analyze these data, we implement a series of behavioral models, based on the generalized matching law, as graphical models, and use computational methods to perform fully Bayesian inference...
February 19, 2019: Journal of the Experimental Analysis of Behavior
Michael E Young
Bayesian approaches to data analysis are considered within the context of behavior analysis. The paper distinguishes between Bayesian inference, the use of Bayes Factors, and Bayesian data analysis using specialized tools. Given the importance of prior beliefs to these approaches, the review addresses those situations in which priors have a big effect on the outcome (Bayes Factors) versus a smaller effect (parameter estimation). Although there are many advantages to Bayesian data analysis from a philosophical perspective, in many cases a behavior analyst can be reasonably well-served by the adoption of traditional statistical tools as long as the focus is on parameter estimation and model comparison, not null hypothesis significance testing...
February 19, 2019: Journal of the Experimental Analysis of Behavior
Russell Taylor, Douglas Elliffe, Christopher A Podlesnik, Sarah Cowie
We introduce to behavior analysis a way of analyzing choice behavior that exploits recent developments in nanoeconomics, financial economics, and econometrics. A response return, modeled on an economic return, is the log differenced count of responses allocated to each of two alternatives during a short time window, compared with that in the immediately preceding window. The response return is a new dependent variable which offers a novel and useful way of looking at operant behavior, especially at the molecular level of analysis...
February 19, 2019: Journal of the Experimental Analysis of Behavior
Christopher T Franck, Mikhail N Koffarnus, Todd L McKerchar, Warren K Bickel
Statistical inference (including interval estimation and model selection) is increasingly used in the analysis of behavioral data. As with many other fields, statistical approaches for these analyses traditionally use classical (i.e., frequentist) methods. Interpreting classical intervals and p-values correctly can be burdensome and counterintuitive. By contrast, Bayesian methods treat data, parameters, and hypotheses as random quantities and use rules of conditional probability to produce direct probabilistic statements about models and parameters given observed study data...
February 19, 2019: Journal of the Experimental Analysis of Behavior
Pier-Olivier Caron
Multilevel modeling has been considered a promising statistical tool in the field of the experimental analysis of behavior and may serve as a convenient statistical analysis for matching behavior because it structures data in groups (or levels) to account simultaneously for the within-subject and between-subject variances. Heretofore, researchers have sometimes pooled data erroneously from different subjects in a single analysis by using average ratios, average response and reinforcer rates, aggregation of subjects, etc...
February 13, 2019: Journal of the Experimental Analysis of Behavior
William Brady DeHart, Brent A Kaplan
Behavior analysis and statistical inference have shared a conflicted relationship for over fifty years. However, a significant portion of this conflict is directed toward statistical tests (e.g., t-tests, ANOVA) that aggregate group and/or temporal variability into means and standard deviations and as a result remove much of the data important to behavior analysts. Mixed-effects modeling, a more recently developed statistical test, addresses many of the limitations of more basic tests by incorporating random effects...
February 13, 2019: Journal of the Experimental Analysis of Behavior
Elizabeth G E Kyonka, Suzanne H Mitchell, Lewis A Bizo
Debates about the utility of p values and correct ways to analyze data have inspired new guidelines on statistical inference by the American Psychological Association (APA) and changes in the way results are reported in other scientific journals, but their impact on the Journal of the Experimental Analysis of Behavior (JEAB) has not previously been evaluated. A content analysis of empirical articles published in JEAB between 1992 and 2017 investigated whether statistical and graphing practices changed during that time period...
February 12, 2019: Journal of the Experimental Analysis of Behavior
Douglas Elliffe, Martin Elliffe
We advocate for rank-permutation tests as the best choice for null-hypothesis significance testing of behavioral data, because these tests require neither distributional assumptions about the populations from which our data were drawn nor the measurement assumption that our data are measured on an interval scale. We provide an algorithm that enables exact-probability versions of such tests without recourse to either large-sample approximation or resampling approaches. We particularly consider a rank-permutation test for monotonic trend, and provide an extension of this test that allows unequal number of data points, or observations, for each subject...
February 7, 2019: Journal of the Experimental Analysis of Behavior
Andrew R Craig, Wayne W Fisher
Randomization statistics offer alternatives to many of the statistical methods commonly used in behavior analysis and the psychological sciences, more generally. These methods are more flexible than conventional parametric and nonparametric statistical techniques in that they make no assumptions about the underlying distribution of outcome variables, are relatively robust when applied to small-n data sets, and are generally applicable to between-groups, within-subjects, mixed, and single-case research designs...
February 1, 2019: Journal of the Experimental Analysis of Behavior
Christopher A Podlesnik, Toshikazu Kuroda, Corina Jimenez-Gomez, Josele Abreu-Rodrigues, Carlos R X Cançado, Abigail L Blackman, Karli Silverman, Jamie Villegas-Barker, Melinda Galbato, Italo S C Teixeira
The present study examined whether resurgence of a previously reinforced target response upon removing alternative reinforcement would be greater when (1) returning to the original training context (ABA context changes) versus (2) remaining in the analogue treatment context in which the alternative response was differentially reinforced (ABB context changes). Experiment 1 arranged reinforcement of button pressing with points exchangeable for money in university students. Experiment 2 arranged reinforcement of lever pressing with food for rats...
February 1, 2019: Journal of the Experimental Analysis of Behavior
Steven Riley, J J McDowell
Regularization, or shrinkage estimation, refers to a class of statistical methods that constrain the variability of parameter estimates when fitting models to data. These constraints move parameters toward a group mean or toward a fixed point (e.g., 0). Regularization has gained popularity across many fields for its ability to increase predictive power over classical techniques. However, articles published in JEAB and other behavioral journals have yet to adopt these methods. This paper reviews some common regularization schemes and speculates as to why articles published in JEAB do not use them...
February 1, 2019: Journal of the Experimental Analysis of Behavior
Kenneth W Jacobs
Randomization tests are a class of nonparametric statistics that determine the significance of treatment effects. Unlike parametric statistics, randomization tests do not assume a random sample, or make any of the distributional assumptions that often preclude statistical inferences about single-case data. A feature that randomization tests share with parametric statistics, however, is the derivation of a p-value. P-values are notoriously misinterpreted and are partly responsible for the putative "replication crisis...
January 30, 2019: Journal of the Experimental Analysis of Behavior
Tyler D Nighbor, Ivori Zvorsky, Allison N Kurti, Joan M Skelly, Warren K Bickel, Derek D Reed, Gideon P Naudé, Stephen T Higgins
Two common behavioral economic simulation tasks used to study cigarette smoking are the Cigarette Purchase Task, a measure of cigarette demand, and delay discounting, a measure of the subjective value of rewards as a function of delays to delivery. Few studies have evaluated whether combining these tasks enhances understanding of smoking beyond either alone. The current study represents an initial evaluation of the intersection between cigarette demand indices and delay discounting among pregnant smokers by examining associations between these measures and whether a woman makes antepartum quit attempts before entering prenatal care (a reliable predictor of eventual quitting)...
January 25, 2019: Journal of the Experimental Analysis of Behavior
Jonathan E Friedel, William B DeHart, Anne M Foreman, Michael E Andrew
Discounting is the process by which outcomes lose value. Much of discounting research has focused on differences in the degree of discounting across various groups. This research has relied heavily on conventional null hypothesis significance tests that are familiar to psychologists, such as t-tests and ANOVAs. As discounting research questions have become more complex by simultaneously focusing on within-subject and between-group differences, conventional statistical testing is often not appropriate for the obtained data...
January 24, 2019: Journal of the Experimental Analysis of Behavior
Greg Jensen
Obtained reinforcement (whether measured as counts or as rates) is frequently used as a predictor in regression analyses of behavior. This approach, however, often contradicts the strict requirement that predictors in a regression be statistically independent of behavior. Indeed, by definition, reinforcement in operant scenarios depends on behavior, creating a causal feedback loop. The consequence of this feedback loop is bias in the estimation of regression parameters. This manuscript describes the technique of instrumental variable estimation (IVE), which allows unbiased regression parameters to be obtained through the use of "instruments," variables that are known a priori to be independent of both compromised predictors and of regression outcomes...
January 24, 2019: Journal of the Experimental Analysis of Behavior
Toshikazu Kuroda, Yuto Mizutani, Carlos R X Cançado, Christopher A Podlesnik
Zebrafish (Danio rerio) are a promising animal model for studying the effects of gene-environment interactions on behavior. Two experiments were conducted to assess punishment effects of presenting predator videos (Indian leaf fish; Nandus nandus) and electric shock on operant approach responses in zebrafish. In Experiment 1, the predator video and shock stimuli were presented upon a response maintained by a single variable-interval schedule of food reinforcement in different groups of fish. In Experiment 2, the predator video and shock stimuli were presented upon one of two response alternatives maintain by concurrently available variable-interval schedules of food reinforcement in different groups of fish...
December 27, 2018: Journal of the Experimental Analysis of Behavior
L Jorge Ruiz-Sánchez, Carmen Luciano, Paul M Guinther
The present investigation used a respondent-type (ReT) training procedure to generate derived false memories. A one-to-many ReT training procedure was implemented in order to establish two stimulus equivalence classes, each consisting of one shape and 24 random words (i.e., Class 1 and Class 2). A partial test for stimulus equivalence with a subset of stimuli from each class followed. Failing an equivalence test resulted in additional ReT training and equivalence testing on new subsets of stimuli. After passing an equivalence test, participants were presented with 12 study-list words from Class 1 for memorization, followed by a distraction task...
December 21, 2018: Journal of the Experimental Analysis of Behavior
Jeffrey M Pisklak, Margaret A McDevitt, Roger M Dunn, Marcia L Spetch
Pigeons chose between two options on a concurrent-chains task with a single response requirement in the initial link. The suboptimal option ended with food 20% of the time whereas the optimal option ended with food 80% of the time. During a Sig-Both condition, terminal-link stimuli on both options signaled whether or not food would occur. During a Sig-Sub condition, terminal-link stimuli on the suboptimal option provided differential signals, but stimuli on the optimal option did not differentially signal the food and no food outcomes...
December 19, 2018: Journal of the Experimental Analysis of Behavior
Tom Byrne, Brianna Sarno
We investigated the duration of lever pressing by rats when the delivery of appetitive reinforcers was contingent upon response duration. In the first experiment, response durations increased when duration requirements were imposed, and they decreased when duration requirements were removed. This effect occurred whether reinforcers were immediate or delayed by 8 s. In order to maintain the integrity of the delay intervals, reinforcer delivery was dependent upon both lever depression and release. In a second experiment, lever depression only and a response duration of at least 4 s were required for reinforcer delivery...
December 18, 2018: Journal of the Experimental Analysis of Behavior
Jonathan E Friedel, Ann Galizio, Meredith S Berry, Mary M Sweeney, Amy L Odum
Relapse is the recovery of a previously suppressed response. Animal models have been useful in examining the mechanisms underlying relapse (e.g., reinstatement, renewal, reacquisition, resurgence). However, there are several challenges to analyzing relapse data using traditional approaches. For example, null hypothesis significance testing is commonly used to determine whether relapse has occurred. However, this method requires several a priori assumptions about the data, as well as a large sample size for between-subjects comparisons or repeated testing for within-subjects comparisons...
December 17, 2018: Journal of the Experimental Analysis of Behavior
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