Use of Brief Instructional Trials to Identify Small Group Reading Strategies: A Two Experiment Study

The Instructional Hierarchy (IH) has proven useful for understanding the functional properties of empirically valid instructional strategies. Investigators have relied heavily on the IH as a heuristic in conceptualizing instructional components used in brief experimental analyses. To date, only one investigation has applied brief experimental analysis results to small group reading interventions. The purpose of this paper is to describe two studies which used single session instructional trials to identify interventions that were subsequently applied to small group reading instruction. In both studies, individualized instructional trials that probed for skill and performance deficits were carried out and results suggested that all students benefited from the instructional intervention. Next, the intervention was implemented in a small group format. In Experiment 2, however, validation of the instructional package was carried out by the classroom teacher who delivered the instructional package to the small group. In both cases, extended experimental analyses suggested that the intervention was effective at improving all participants’ generalized reading fluency. Results of both studies are discussed in terms of how future studies can refine procedures for validating instructional and motivational components before classroom applications.     

THE IMPACT OF FUNCTIONAL ANALYSIS METHODOLOGY ON OUTPATIENT CLINIC SERVICES

The impact of the article by Iwata, Dorsey, Slifer, Bauman, and Richman (1982) on research in severe behavior disorders has been impressive. Equally impressive, however, but not as fully recognized, has been the impact of this methodology on the routine professional activities of those who employ functional analysis methods in their daily work. As one example of this impact, we describe the evolution of assessment procedures based on “brief functional analysis” methodology in our outpatient clinics. Less apparent have been the collateral effects that occur from using these procedures. Interactions with clients and colleagues have changed in ways that result in increased positive reinforcement. In this article, we briefly discuss the positive impact functional analysis has had on one specific work behavior—outpatient clinic assessment—and describe some of the generalized effects we have experienced in related aspects of our daily professional activities.     

Brief Experimental Analysis of Spanish Reading Fluency: An Exploratory Evaluation

Brief experimental analyses of reading fluency are useful for identifying effective interventions for improving reading fluency. The current study extends previous research by conducting an exploratory evaluation of brief experimental analyses of reading fluency for Spanish reading. A 10-year old Hispanic male presented with reading fluency deficits for English and Spanish reading. Brief experimental analyses of English and Spanish reading identified distinct interventions for each which increased oral reading fluency. Intervention procedures evaluated during brief experimental analyses included listening passage preview, repeated readings, and reward. Replication of analyses was conducted to examine changes in instructional need over time. For English reading, the intervention identified during the initial analysis (i.e., listening passage preview with repeated readings) was identified as the most effective when the analysis was replicated. For Spanish reading, listening passage preview was identified as the most effective intervention during the initial analysis, while repeated readings was identified as most effective when the analysis was replicated. Results are discussed in terms of future research given the exploratory nature of the current study.     

Using Brief Experimental Analysis to Select Oral Reading Interventions: An Investigation of Treatment Utility

This study examined the treatment utility of brief experimental analysis for selecting skill-based oral reading interventions that targeted acquisition and fluency. Two second and one third grade student served as participants. The potentially most and least effective instructional packages identified from the brief experimental analysis for each student were alternated during an extended analysis phase. The instructional components that were compared were based on an ease of implementation hierarchy, with the brief experimental analysis used to select the hypothesized most effective instructional package for oral reading. Visual analysis of extended analysis data revealed that the hypothesized most effective combination of instructional components identified from the brief analysis produced greater initial gains in reading for two children (i.e., over 29 and 21 intervention days) and greater gains in reading throughout the extended analysis phase for the third child. Thus, the investigation provided preliminary evidence for the treatment utility of using brief experimental analysis to select effective and efficient oral reading instructional interventions. Implications, limitations, and future research topics are discussed.     

Multivariate multiple regression analyses: a permutation method for linear models

A multivariate extension of a univariate procedure for the analysis of experimental designs is presented. A Euclidean-distance permutation procedure is used to evaluate multivariate residuals obtained from a regression algorithm, also based on Euclidean distances. Applications include various completely randomized and randomized block experimental designs such as one-way, Latin square, factorial, nested, and split-plot designs, with and without covariates. Unlike parametric procedures, the only required assumption is the randomization of subjects to treatments.     

Visual aids and structured criteria for improving visual inspection and interpretation of single-case designs

Because behavior analysis is a data-driven process, a critical skill for behavior analysts is accurate visual inspection and interpretation of single-case data. Study 1 was a basic study in which we increased the accuracy of visual inspection methods for A-B designs through two refinements of the split-middle (SM) method called the dual-criteria (DC) and conservative dual-criteria (CDC) methods. The accuracy of these visual inspection methods was compared with one another and with two statistical methods (Allison & Gorman, 1993; Gottman, 1981) using a computer-simulated Monte Carlo study. Results indicated that the DC and CDC methods controlled Type I error rates much better than the SM method and had considerably higher power (to detect real treatment effects) than the two statistical methods. In Study 2, brief verbal and written instructions with modeling were used to train 5 staff members to use the DC method, and in Study 3, these training methods were incorporated into a slide presentation and were used to rapidly (i.e., 15 min) train a large group of individuals (N = 87). Interpretation accuracy increased from a baseline mean of 55% to a treatment mean of 94% in Study 2 and from a baseline mean of 71% to a treatment mean of 95% in Study 3. Thus, Study 1 answered basic questions about the accuracy of several methods of interpreting A-B designs; Study 2 showed how that information could be used to increase the accuracy of human visual inspectors; and Study 3 showed how the training procedures from Study 2 could be modified into a format that would facilitate rapid training of large groups of individuals to interpret single-case designs.     

Using confidence intervals for graphically based data interpretation.

As a potential alternative to standard null hypothesis significance testing, we describe methods for graphical presentation of data--particularly condition means and their corresponding confidence intervals--for a wide range of factorial designs used in experimental psychology. We describe and illustrate confidence intervals specifically appropriate for between-subject versus within-subject factors. For designs involving more than two levels of a factor, we describe the use of contrasts for graphical illustration of theoretically meaningful components of main effects and interactions. These graphical techniques lend themselves to a natural and straightforward assessment of statistical power.     

Bayesian factor analysis for multilevel binary observations

Multilevel covariance structure models have become increasingly popular in the psychometric literature in the past few years to account for population heterogeneity and complex study designs. We develop practical simulation based procedures for Bayesian inference of multilevel binary factor analysis models. We illustrate how Markov Chain Monte Carlo procedures such as Gibbs sampling and Metropolis-Hastings methods can be used to perform Bayesian inference, model checking and model comparison without the need for multidimensional numerical integration. We illustrate the proposed estimation methods using three simulation studies and an application involving student's achievement results in different areas of mathematics. The authors thank Ian Westbury, University of Illinois at Urbana Champaign for kindly providing the SIMS data for the application.     

FUNCTIONAL ANALYSIS OF SEPARATE TOPOGRAPHIES OF ABERRANT BEHAVIOR

We conducted a functional analysis of distinct topographies of aberrant behavior displayed by 4 clients. We first analyzed the behaviors in an aggregate fashion and then separated the behaviors to formulate hypotheses about the maintaining variables for each behavior. The procedures were used in a two-phase experiment. During Phase 1, two extended functional analyses were completed, one in an inpatient unit and one in a special education classroom. During Phase 2, two brief functional analyses were completed in an outpatient clinic. Results indicated that hypotheses of separate functions for distinct behaviors can be generated using both extended and brief functional analyses when the results are graphed in the aggregate and are separated by response topography. The results also suggest that these methods can improve the accuracy of data interpretation and treatment selection.     

Functional magnetic resonance imaging: Overview and methods for psychological research

Functional magnetic resonance imaging (fMRI) allows noninvasive imaging of hemodynamic changes related to neural activity. This technique can be used in single-subject designs and can provide millimeter spatial resolution and temporal resolution in the range of 5–10 sec. This paper provides a brief introduction to MRI techniques and their application to functional neuroimaging, focusing on methodological issues that are of particular concern to psychologists, including methods for presenting computerized stimuli to subjects without disrupting the scanner, experimental design issues, and statistical analysis and image processing procedures. To illustrate methodological issues, recent results from a series of studies looking at the topographic organization of visual cortex are presented. General issues concerning limitations in this technique, future directions in its development, its relationship to other neuroimaging techniques, and the role of functional neuroimaging in psychological research are addressed in the Discussion.     

The consecutive controlled case series: Design,data-analytics,and reporting methods supporting the study of generality

Single-case experimental designs (SCEDs) have proven invaluable in research and practice because they are optimal for asking many experimental questions relevant to the analysis of behavior. The consecutive controlled case series (CCCS) is a type of study in which a SCED is employed in a series of consecutively encountered cases that undergo a common procedure or share a common characteristic. Additional design elements, data-analytic, and reporting methods enable researchers to ask experimental questions relevant to the study of generality of procedures and processes. The current paper discusses the CCCS methodologies, including the retrospective, prospective, and randomized CCCS. These methodologies can be applied to examine the generality of clinical procedures (including their general efficacy, the limits of their generality, and variables that may mediate generality); study the epidemiology and phenomenology of clinical problems; and compare the efficacy of 2 clinical procedures within a randomized controlled trial combining SCEDs with randomized group designs.     

Statistical inference based on ranks

This paper develops a unified approach, based on ranks, to the statistical analysis of data arising from complex experimental designs. In this way we answer a major objection to the use of rank procedures as a major methodology in data analysis. We show that the rank procedures, including testing, estimation and multiple comparisons, are generated in a natural way from a robust measure of scale. The rank methods closely parallel the familiar methods of least squares, so that estimates and tests have natural interpretations.This research was supported in part by grant MCS76-07292 from the National Science Foundation.     

Refining the experimental analysis of academic skills deficits: part II. Use of brief experimental analysis to evaluate reading fluency treatments

The technology of brief experimental analysis is just beginning to be used for identification of effective treatments for individual students who experience difficulty with oral reading fluency. In this study, the effect of a reading fluency treatment package was examined on easy and hard passages, and generalization was assessed on passages with high content overlap. The results suggest that the treatment package increased reading fluency for all 3 students. Effects were moderated by difficulty level for all 3 students. Results are discussed in terms of future refinements to the procedures, validation of the methods, and potential applications in clinical and school settings.     

A computational model of visual analogies in design

We present an analysis of the work of human participants in addressing design problems by analogy. We describe a computer program, called Galatea, that simulates the visual input and output of four experimental participants. Since Galatea is an operational computer program, it makes specific commitments about the visual representations and reasoning it uses for analogical transfer. In particular, Galatea provides a computational model of how human designers might be generating new designs by incremental transfer of the problem-solving procedure used in previous design cases.     

125 years of the American Journal of Psychology: a historical overview

The American journal of Psychology celebrates 125 years of publication this year. From its inception, the Journal has attempted to record and communicate the results of research conducted in laboratories of psychology. It has also provided its readers with laboratory plans and designs for apparatus for research and demonstrations and described experimental procedures to facilitate the conduct of research. Its attention to reviews of books over a wide range of psychological topics and its inclusion of articles that provide historical perspectives on the development of psychology and its concerns broaden the context in which laboratory research is carried out. This brief overview of the Journal's history offers a perspective on the role of the Journal in, and its contributions to, the development of scientific psychology.     

It has been said that, “There are three degrees of falsehoods: Lies,damn lies,and statistics”

Applied behavior analysis (ABA) researchers have historically eschewed population-based, inferential statistics, preferring to conduct and analyze repeated observations of each participant's responding under carefully controlled and manipulated experimental conditions using single-case designs (SCDs). In addition, early attempts to adapt traditional statistical procedures for use with SCDs often involved trade-offs between experimental and statistical control that most ABA researchers have found undesirable. The statistical methods recommended for use with SCDs in the current special issue represent a welcome departure from such prior suggestions in that the current authors are proposing that SCD researchers add statistical methods to their current practices in ways that do not alter traditional SCD practices. Further refinement and use of such methods would (a) facilitate the inclusion of research using SCDs in meta-analyses and (b) aid in the development and planning of grant-funded research using SCD methods. Collaboration between SCD researchers and statisticians, particularly on research that demonstrates the benefit of these methods, may help promote their acceptance and use in ABA.     

ANALYSIS OF REPEATED MEASURES AND OTHER DESIGNS

For small and balanced analysis of variance problems, standard computer programs are convenient and efficient. For large problems, regression pro- grams are at least competitive with analysis of variance programs; and, when a problem is unbalanced, they usually provide the only reasonable solution. This paper discusses procedures for using regression programs for the computing of analyses of variance. A procedure for coding matrices is described for experimental designs having nested and crossed factors. Several illustrations are given, and the limitation of the procedure with large repeated measures designs is discussed. A second algorithm is offered for obtaining the sums of squares for nested factors and their interactions in such designs.