Images: Preliminary scale construction

Abstract

In a series of papers, Bagarozzi and Giddings outlined a theoretical model of mate selection and marital interaction based upon principles of cognitive matching (Bagarozzi, 1982, 1986; Bagarozzi&Giddings, 1983, 1984). Briefly, this theory postulates that individuals seek out, develop intimate relationships with, and eventually marry persons whom they perceive to: (a) possess specific personality traits, qualities and characteristics; (b) share similar values, beliefs, and ideas concerning husband/wife roles; and (c) subscribe to a similar set of rules and assumptions governing interpersonal power, distributive justice, and the exchange of value messages between intimates. Essentially, one marries a person whom he/she perceives to fit an internal cognitive model or schema of an “ideal spouse.” The term “ideal” does not denote perfection. It merely represents an enduring image that becomes a standard against which all prospective mates are judged and evaluated. This cognitive matching takes place at both conscious and unconscious levels of awareness.     

An R package for state-trace analysis

State-trace analysis (Bamber, Journal of Mathematical Psychology, 19, 137-181, 1979) is a graphical analysis that can determine whether one or more than one latent variable mediates an apparent dissociation between the effects of two experimental manipulations. State-trace analysis makes only ordinal assumptions and so, is not confounded by range effects that plague alternative methods, especially when performance is measured on a bounded scale (such as accuracy). We describe and illustrate the application of a freely available GUI driven package, StateTrace, for the R language. StateTrace automates many aspects of a state-trace analysis of accuracy and other binary response data, including customizable graphics and the efficient management of computationally intensive Bayesian methods for quantifying evidence about the outcomes of a state-trace experiment, developed by Prince, Brown, and Heathcote (Psychological Methods, 17, 78-99, 2012).     

An R package for single-case randomization tests

Randomization tests are nonparametric statistical tests that obtain their validity by computationally mimicking the random assignment procedure that was used in the design phase of a study. Because randomization tests do not rely on a random sampling assumption, they can provide a better alternative than parametric statistical tests for analyzing data from single-case designs. In this article, an R package is described for use in designing single-case phase (AB, ABA, and ABAB) and alternation (completely randomized, alternating treatments, and randomized block) experiments, as well as for conducting statistical analyses on data gathered by means of such designs. The R code is presented in a step-by-step way, which at the same time clarifies the rationale behind single-case randomization tests.     

An Apple II package for computer-assisted telephone interviewing

This paper describes an Apple II (an Apple-compatible) microcomputer package for a computer-assisted telephone interviewing (CATI) system. This system generates random telephone numbers within any number of exchanges that the user supplies, automatically dials the telephone, prompts the interviewer with each question, and records and permanently saves each response. It also provides a printed copy of the collected data by frequency of response in each question category. The Apple II CATI package is readily available, inexpensive, and easy to program in the BASIC language.     

Mousetrap: An integrated,open-source mouse-tracking package

Mouse-tracking – the analysis of mouse movements in computerized experiments – is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os.     

On use of student samples for scale construction

This research note responds to the question of whether a convenience sample of undergraduate students may be successfully utilized in concept development and in scale construction, and in what way the results are comparable to the findings of a representative national sample. The results of a Mokken analysis in both samples support the hypothesis that convenience samples have utility in concept development and in developing measures that can also be used in representative samples.     

THRIFTNET: An economical software package for interprocessor communications

THRIFTNET is a collection of programs created in response to the need to share computer resources across computer systems on the campus of the University of Mississippi. Using THRIFTNET, files may be transferred between machines so that devices and programs available on only selected systems may be used to process information collected on any machine. File transfer is accomplished in small blocks of 128 data bytes embedded in a modified bisynch protocol that checks for transmission errors. The direction of transfer is dictated by the user, so files on small machines may be sent to large machines and files on large machines may be received by small machines.     

An R package to compute commonality coefficients in the multiple regression case: An introduction to the package and a practical example

Multiple regression is a widely used technique for data analysis in social and behavioral research. The complexity of interpreting such results increases when correlated predictor variables are involved. Commonality analysis provides a method of determining the variance accounted for by respective predictor variables and is especially useful in the presence of correlated predictors. However, computing commonality coefficients is laborious. To make commonality analysis accessible to more researchers, a program was developed to automate the calculation of unique and common elements in commonality analysis, using the statistical package R. The program is described, and a heuristic example using data from the Holzinger and Swineford (1939) study, readily available in the MBESS R package, is presented.     

TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling

Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution. We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.     

Coping through emotional approach: scale construction and validation

Four studies demonstrate the psychometric adequacy and validity of scales designed to assess coping through emotional approach. In separate undergraduate samples, exploratory and confirmatory factor analyses of dispositional (Study 1) and situational (Study 3) coping item sets yielded 2 distinct emotional approach coping factors: emotional processing (i.e., active attempts to acknowledge and understand emotions) and emotional expression. The 2 scales yielded high internal consistency and test-retest reliability, as well as convergent and discriminant validity. A study (Study 2) of young adults and their parents established the scales' interjudge reliabilities. Longitudinal (Study 3) and experimental (Study 4) research supported the predictive validity of the emotional approach coping scales with regard to adjustment to stressful encounters. Findings highlight the utility of functionalist theories of emotion as applied to coping theory.     

The construction and validation of a juror bias scale

A questionnaire was constructed to measure individual differences in pretrial bias among jurors. The final Likert scale, called the Juror Bias Scale (JBS), contains 17 items—8 that reflect pretrial expectancies that defendants, in general, commit the crimes with which they are charged and 9 that reflect the value attached to conviction and punishment. The scale is internally consistent and test-retest reliable. Scores are uncorrelated with social desirability, moderately correlated with I-E control and belief in a just world, and more highly correlated with authoritarianism. In one validation experiment, student jurors were exposed to three trial presentations in a laboratory setting. Overall, subjects classified as prosecution biased were more conviction prone and adopted a less stringent standard of reasonable doubt. In a second study, community jurors watched one of two videotaped mock trials in a courtroom. Prosecution-biased subjects asserted a higher probability that the defendent committed the crime and rendered a higher percentage of guilty verdicts than defense-biased subjects for one of the two trials. JBS scores were unrelated to all demographic variables, but were significantly correlated with political views. The potential uses and limitations of the JBS are discussed.     

RMediation: An R package for mediation analysis confidence intervals

This article describes the RMediation package,which offers various methods for building confidence intervals (CIs) for mediated effects. The mediated effect is the product of two regression coefficients. The distribution-of-the-product method has the best statistical performance of existing methods for building CIs for the mediated effect. RMediation produces CIs using methods based on the distribution of product, Monte Carlo simulations, and an asymptotic normal distribution. Furthermore, RMediation generates percentiles, quantiles, and the plot of the distribution and CI for the mediated effect. An existing program, called PRODCLIN, published in Behavior Research Methods, has been widely cited and used by researchers to build accurate CIs. PRODCLIN has several limitations: The program is somewhat cumbersome to access and yields no result for several cases. RMediation described herein is based on the widely available R software, includes several capabilities not available in PRODCLIN, and provides accurate results that PRODCLIN could not.     

Acquiescence and response skewness in scale construction: a paradox

Kirton's version of the Wilson C Scale is primarily a version wherein items of the C Scale that attract very skewed responses have been eliminated. Contrary to what seems obvious, it is shown that the Kirton scale shows more, rather than less, influence from acquiescent response bias. Although such influence was not a serious problem with this particular scale, the finding does give grounds for believing that some skewed items may make a valuable contribution to an additive (‘Likert’) scale.     

An instructional package to teach communication behaviors in a classroom setting

An instructional package consisting of modeling, written and behavioral rehearsal, and feedback was used to teach communication behaviors (simple sentence responses, information responses, and eye contact) to 17 emotionally handicapped students, ages ranging between 11 and 17 years. A multiple baseline analysis indicated that the communication behaviors targeted for training increased significantly following implementation of the instructional package. These behaviors also generalized across settings and nontrained questions and were maintained across time. Finally, the average amount of training time required for each subject was 2 hours, indicating that the use of the instructional package in a classroom setting was economical. These results show that communication behaviors can be delivered effectively and economically in a classroom setting.     

An interactive gaming package for teaching and research in interdependent choice

A pair of FORTRAN programs allows two individuals or groups to play prisoner’s dilemma and other two-party mixed-motive games on physically isolated terminals of a time-sharing computer. The programs provide a flexible tool for teaching and research through a series of programmable options for structuring and enhancing the playing environment of the game. Four participatory roles for students provide an opportunity for integrated exposure to the broader context of empirical research design and execution.