- 216.238.99.111. It is clear that we cannot claim that these assumptions are always valid for multiple baseline designs. The purposes of this article are to (1) thoroughly examine the impact that threats to internal validity can have on concurrent and nonconcurrent multiple baseline designs; (2) describe the critical features of each design type that control for threats to internal validity; and (3) offer recommendations for use and reporting of concurrent and nonconcurrent multiple baseline designs. However, the specific issues in this controversy have never been thoroughly identified, discussed, and resolved; and instead a consensus emerged without the issues being explicitly addressed. Journal of Consulting & Clinical Psychology, 49(2), 193211. The vast majority of contemporary published multiple baseline designs describe the timing of phases in terms of sessions rather than days or dates. Google Scholar. As we mentioned above, across-tier comparisons require the assumptions that coincidental events will (1) contact and (2) have similar effects on all tiers of the design. Nonconcurrent multiple baseline designs and the evaluation of educational systems. Addressing the second question requires data analysis that is informed by the specifics of the study. These could include presence of observers, testing procedures, exposure to testing stimuli, attention from implementers, being removed from the typical setting, exposure to a special setting, and so on. Given this dilemma, priority should be given to optimizing the within-tier comparisons because this is the comparison that can confer stronger control. They state, the nonconcurrent multiple baseline across participants design is inherently weaker than other multiple baseline design variations. However, this kind of support is not necessary: lagged replications of baseline predictions being contradicted by data in the treatment phase provide strong control for all of these threats to internal validity. Events that contact a single participant may be termed participant-level. https://doi.org/10.1016/0005-7916(81)90055-0, Wolfe, K., Seaman, M. A., & Drasgow, E. (2016). Consequently, it is often difficult or impossible to dismiss rival hypotheses or explanations. Single-case research designs: Methods for clinical and applied settings (3rd ed.). The authors discuss two designs commonly used to demonstrate reliable control of an important behavior change (p. 94). The authors argue that like the concurrent multiple baseline design, the nonconcurrent form can rule out coincidental events (i.e., history) as a threat to internal validity and that experimental control can be established by the replication of the within-tier comparison with phase changes offset relative to the beginning of baseline. For example, in a multiple baseline across settings, the settings could present somewhat different demands. A given period of maturation may affect various participants, various behaviors, or behaviors in various settings in different ways. The reversal model is fine for many questions, but in some instances, removing a type of treatment could be unwise or even unethical. A coincidental event may contact a single unit of analysis (e.g., one of four participants) or multiple units (e.g., all participants). must have stable baseline and tx in first bx (Our specification of phase change offset in terms of real time, days in baseline, and sessions in baseline is unusual. The across-tier comparison is an additional basis for evaluating alternative explanations. Data from the treatment phase in one tier can be compared to corresponding baseline data in another tier. https://doi.org/10.1177/0741932512452794, Lanovaz, M. J., & Turgeon, S. (2020). Behavior Therapy, 6(5), 601608. This assumption was initially identified by Kazdin and Kopel in 1975, but its implications for the rigor of the across-tier comparison have rarely been discussed since that time. These baseline-treatment comparisons, which we will refer to as tiers, differ from one another with respect to participants, behaviors, settings, stimulus materials, and/or other variables. Second, in a remarkably understated reference to the across-tier comparison, Baer et al. Any of these types of circumstances may require additional tiers in order to clearly address threats to internal validity. On resolving ambiguities of the multiple-baseline design: Problems and recommendations. In this highly influential early textbook on SCD, Hersen and Barlow describe only the across-tier analysis and fail to mention replicated within-tier comparisons. Journal of Applied Behavior Analysis, 30(3), 533544. However, ina concurrent multiple baseline across settings a setting-level event would contact only a single tierthe design would be inherently insensitive to these coincidental events. WebLike RCTs, the multiple baseline design can demonstrate that a change in behavior has occurred, the change is a result of the intervention, and the change is significant. Single case experimental design and empirical clinical practice. Remedial and Special Education, 34(1), 2638. We can identify at least three general categories of issues that influence the number of tiers required to render threats implausible: challenges associated with the phenomena under study, experimental design features, and data analysis issues. Houghton Mifflin. Every multiple baseline design in which potential treatment effects are observed in some but not all tiers demonstrates that tiers are not always equally sensitive to interventions. Barlow, D. H., Nock, M. K., & Hersen, M. (2009). Perspectives on Behavior Science Pearson Education. WebAB design advantages - -simple to use AB design disadvantages - -cannot be used to make a confident assumption of a functional relation -vulnerable to confounding variables -does not provide for replication AB design - basic single subject design AB design has two phases of design - A: Baseline B: Intervention Reversal Design referred to as - Johnston, J. M., Pennypacker, H. S., & Green, G. (2010). These coincidental events would contact all tiers of a multiple baseline that include this individual participant, but not tiers that do not involve this participant. Advantages and Disadvantages of ABA Design. Oxford University Press. https://doi.org/10.1007/s40614-022-00326-1, DOI: https://doi.org/10.1007/s40614-022-00326-1. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. For example, phase changes in two consecutive tiers may be lagged by three sessions, but if one to three sessions are conducted per day, the baseline phases could include the same number of days (problem for controlling maturation) and the phase change could occur on the same day in both tiers (problem for controlling coincidental events). https://doi.org/10.1007/s40614-022-00343-0, DOI: https://doi.org/10.1007/s40614-022-00343-0. Recognizing these three dimensions of lag has implications for reporting multiple baseline designs. Single-case intervention research design standards. This has at least two effects: first, the multiple baseline is seen as weaker than the withdrawal design because of this dependence on the across-tier analysis; and second, when nonconcurrent multiple baseline designs are introduced years later, their rigor will be understood by many methodologists in terms of control by across-tier comparisons only, without consideration of replicated within-tier comparisons. The multiple baseline design is useful for interventions that are irreversible due to learning effects, and when treatment cant be withdrawn. In general, a longer lag is better because it reduces the chance that an event could impact multiple tiers. https://doi.org/10.4324/9781315150666, Chapter If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The ABA or Reversal Design An important drawback of pre-experimental designs is that they are subject to numerous threats to their validity. This argument rests on the assumptions that any extraneous variable that affects one tier will (1) contact all tiers and (2) have a similar effect on all tiers. Department of Educational Psychology, Neag School of Education, University of Connecticut, Storrs, CT, 06269, USA, You can also search for this author in After implementing the treatment for the first tier, they say, rather than reversing the just produced change, he instead applies the experimental variable to one of the other as yet unchanged responses. The general steps for the development of the line graphs are as follows: 1. Given that multiple baseline designs make up such a large proportion of the existing SCD literature and current research activity, it is critical that SCD researchers thoroughly understand the specific ways that multiple baseline designs address potential threats to internal validity so that they can make experimental design decisions that optimize internal validity and accurately evaluate, discuss, and interpret the results of their research. This would draw attention to the relationship between the prediction from baseline and the (possible) contradiction of that prediction by the obtained treatment-phase data, and the replication of this prediction-contradiction pair in subsequent tiers. The within-tier comparison may be further strengthened by increasing independence of the tier in other dimensions. WebMultiple-Baseline Designs There are two potential problems with the reversal designboth of which have to do with the removal of the treatment. The dimension of time is recognized in the requirement that phase changes be lagged in real timethat is, the date on which the phase changes are made. However, current practice provides little or no direct information on either the temporal duration (e.g., number of days) of baseline nor the offset between phase changes in real time (i.e., number of calendar days between phase changes). PubMed Central One is that if a Hayes argued that fortunately the logic of the strategy does not really require (p. 206) an across-tier comparison because the within-tier comparison rules out these threats. The bottom line is that the experimenter can never know whether a coincidental event has contacted only a single tier of a concurrent multiple baseline and, therefore, whether it is possible for the across-tier comparison to detect this threat. Further, for both types of multiple baselines, the threat of coincidental events should be evaluated primarily based on replicated within-tier comparisons. They do not elaborate on the importance of this type of comparison. Finally, we make recommendations for more rigorous use, reporting, and evaluation of multiple baseline designs. The first is the reversal design and the authors describe the important applied limitation with this designsituations in which reversals are not possible or feasible in applied settings. In this section, we examine how within- and across-tier comparisons may support (or fail to support), internal validity in concurrent and nonconcurrent multiple baseline designs. https://doi.org/10.1002/bin.1510. Taplin, P. S., & Reid, J. Single-case experimental designs: A systematic review of published research and current standards. Although many maturational changes are gradual, more sudden changes are possible. For example, knowing the date of session 10 in tier 1 tells us nothing about the date of session 10 in tier 2. Effects of instructional set and experimenter influence on observer reliability. Part of Springer Nature. In order to meet the terms of the definition, and confirm the critical characteristics for controlling threats to internal validity, we recommend that all multiple baseline studies explicitly report, for each tier, the number of days and sessions in each phase, and the number of calendar days of phase change lag from the previous tier. In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. Any one tier may, at best, demonstrate a potential treatment effect; however, a set of three or more tiers may strongly address the threat of coincidental events and clearly demonstrate experimental control. And researchers generally design and implement interventions, select tiers, and employ measures that will likely show consistent treatment effects. Kazdin, A. E. (2021). https://doi.org/10.1016/S0005-7894(75)80181-X, Kratochwill, T. R., Hitchcock, J., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M., & Shadish, W. R. (2013). Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery, M. (2005). If a potential treatment effect is seen in one tier, the researcher cannot refer to data from the same day in an untreated tier because the tiers are not synchronized in real time and may not even overlap in real time. Instead, a detailed understanding of how specific threats to internal validity are addressed in multiple baseline designs and specific design features that strengthen or weaken control for these threats are needed. Longer lags and more isolated tiers can reduce the number of tiers necessary to render extraneous variables implausible explanations of results. https://doi.org/10.4324/9781315537085. Thus, although the across-tier analysis does provide a test of the maturation threat, a lack of change in untreated tiers cannot definitively rule it out. Carr (2005) invokes this prediction, verification, and replication logic, and concludes, The nonconcurrent MB design only controls for threats associated with maturation/exposure; it does not control for historical [coincidental events] threats to internal validity, as does a concurrent MB design (p. 220). In general, in a concurrent multiple baseline design across any factor, the across-tier analysis is inherently insensitive to coincidental events that are limited to a single tier of that factor. Journal of Applied Behavior Analysis, 1(1), 9197. Controlling for maturation requires baseline phases of distinctly different temporal durations (i.e., number of days); controlling for testing and session experience requires baseline phases of substantially different number of sessions; and controlling for coincidental events requires phase changes on sufficiently offset calendar dates. WebIn yet a third version of the multiple-baseline design, multiple baselines are established for the same participant but in different settings. WebGive two advantages and two disadvantages of quasi-experimental designs. Further, it is impossible to know how many events, which events, or the severity of the events that are missed by an across-tier comparison. The across-tier comparison is valuable primarily when it suggests the presence of a threat by showing a change in an untreated tier at approximately the same time (i.e., days, sessions, or dates) as a potential treatment effect. The assumption that maturation contacted all tiers is strongparticipants were all exposed to maturational variables (i.e., unidentified biological events and environmental interactions) for the same amount of time. Create the data table in Sheets; 2. Harvey, M. T., May, M. E., & Kennedy, C. H. (2004). Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Nonconcurrent designs are said to be substantially compromised with respect to internal validity and in general this limitation is ascribed to their supposed weakness in addressing threats of coincidental events (i.e., history). To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Part of Springer Nature. Therefore, we believe that these features should be explicitly included in the definition of multiple baseline designs. For example, it is implausible that the effects of maturation would coincide with a phase change after 5 days in one tier, after 10 days in a second tier, and after 15 days in a third. Concurrent multiple baseline designs are multiple baseline designs in which the tiers are synchronized in real time.
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