because a non-concurrent design does not allow any AB comparisons across baselines, it omits the opportunity to see if responding under the control condition changes when the treatment condition is implemented in the other baseline. In both forms of multiple baseline designs, a potential treatment effect in the first tier would be vulnerable to the threat that the changes in data could be a result of testing or session experience. The authors discuss two designs commonly used to demonstrate reliable control of an important behavior change (p. 94). chapter 9 Flashcards | Quizlet Hayes, S. C. (1981). 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. Although the design entails two of the three elements of baseline logicprediction and replicationthe absence of concurrent baseline measures precludes the verification of [the prediction]. Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). 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 lag between phase changes must be long enough that maturation over any single amount of time cannot explain the results in multiple tiers. Attachment L: Strengths and Limitations of the Single WebNew Mexico's Flagship University | The University of New Mexico PubMedGoogle Scholar. If this patterna clear prediction from baseline being contradicted when and only when the independent variable is introducedcan be replicated across additional tiers of the multiple baseline, then the evidence of a treatment effect is incrementally strengthened. A critical requirement of the within-tier analysis is that no single extraneous event could plausibly cause the observed changes in multiple tiers. These reports do not provide the information necessary to rigorously evaluate maturation or coincidental events. Oxford. https://doi.org/10.1177/001440290507100203, Johnston, J. M., Pennypacker, H. S., & Green, G. (2020). The vast majority of contemporary published multiple baseline designs describe the timing of phases in terms of sessions rather than days or dates. disadvantages Further, if the potential treatment effect is more gradual (as one might expect from an educational intervention on a complex skill), maturational changes may be impossible to distinguish from treatment effects. Correspondence to It is possible that a coincidental event may be present for all tiers but have different effects on different tiers. The point is that although the across-tier comparison may reveal a maturation effect, there are also circumstances in which it may fail to do so. For example, two rooms in the same treatment center would share more coincidental events than a room in a treatment center and another room at home. The Nonconcurrent Multiple-Baseline Design: It is What it is and Not Something Else. Concurrent and nonconcurrent multiple baseline designs address maturation in virtually identical ways through both within- and across-tier comparisons. We can strongly argue that all tiers contact testing and session experience during baseline because we schedule and conduct these sessions. The across-tier comparison provides another possible source of control for maturation. For the purposes of this article, we define a multiple baseline design as a single-case experimental design that evaluates causal relations through the use of multiple baseline-treatment comparisons with phase changes that are offset in (1) real time (e.g., calendar date), (2) number of days in baseline, and (3) number of sessions in baseline. Research methodologists have identified numerous potential alternative explanations that are threats to internal validity (e.g., Campbell & Stanley, 1963; Cooper et al., 2020; Kazdin, 2021; Shadish et al., 2002). As we argued above, the observation of no change in an untreated tier is not strong evidence against a coincidental event affecting the treated tier. In this case, the across-tier comparison would give the false appearance of strong internal validity. A functional relation can be inferred if the pattern of data demonstrates experimental controlthe experimenters ability to produce a change in the dependent variable in a precise and reliable fashion (Sidman, 1960). 7. 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. With control for coincidental events in multiple baseline designs resting squarely on replicated within-tier comparisons, there is no basis for claiming that, in general, concurrent designs are methodologically stronger than nonconcurrent designs. For example, in a multiple baseline across settings, the settings could present somewhat different demands. It would be an even greater concern if the treatment were an instructional program that requires several weeks or months to implement. However, it does not rule out maturation as an alternative explanation of the change in behavior. Web14 : A multiple-baseline design requires that the targeted behavior return to baseline levels when the treatment is removed. 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. Maturational changes may be smooth and gradual, or they may be sudden and uneven. WebA multiple baseline design across behaviors was used to examine intervention effects. However, if this within-tier pattern is replicated in multiple tiers after differing numbers of baseline sessions, this threat becomes increasingly implausible. With stable data, the range within which future data points will fall is (2011). 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). 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). Barlow, D. H., Nock, M. K., & Hersen, M. (2009). Webtreatment (Kazdin & Nock, 2003). Single-case designs for educational research. For example, knowing the date of session 10 in tier 1 tells us nothing about the date of session 10 in tier 2. They do not mention the across-tier comparison, presumably because they believe that this analysis is not necessary to establish experimental control. Ten sessions of baseline would be expected to have similar effects whether they occur in January or June. The tutorial begins with instructions for how to create a simple multiple condition/phase (e.g., withdrawal research design) line graph. Harvey, M. T., May, M. E., & Kennedy, C. H. (2004). Experimental and quasi-experimental designs for generalized causal inference. Multiple baseline designsboth concurrent and nonconcurrentare the predominant experimental design in modern applied behavior analytic research and are increasingly employed in other disciplines. Journal of Applied Behavior Analysis, 1(1), 9197. Hayes, S. C. (1985). This provides clear information about the number of sessions that precede the phase change in each tier, and therefore constitutes a strong basis for controlling the threat of testing and session experience. The functional answer to this question is that there must be sufficient tiers so that none of the threats to internal validity are plausible explanations for the pattern of effects across the set of tiers. In the end, judgments about the plausibility of threats and number of tiers needed must be made by researchers, editors, and critical readers of research. Multiple baseline procedure. WebDisadvantage: Covariance among subjects may emerge if individuals learn vicariously through the experiences of other subjects Also, identifying multiple subjects in the same and (2) Was any change the result of the independent variable? Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery, M. (2005). Thus, to demonstrate experimental control, the effects of the independent variable must not generalize; and to detect an extraneous variable through the across-tier comparison, the effects of that extraneous variable must generalize. (1975). This question cannot be addressed by data analysis alone; any pattern of data, no matter how dramatic, could be a result of an extraneous variable if the experimental design features are not properly arranged. PubMed Central A multiple baseline design with tiers conducted at different times during each day could show disruption due to this coincidental event in the tier assessed early in the day but not in tiers that are assessed later in the day. If the pattern of change shortly after implementation of the treatment is replicated in the other tiers after differing lengths of time in baseline (i.e., different amounts of maturation), maturation becomes increasingly implausible as an alternative explanation. Use of brief experimental analyses in outpatient clinic and home settings. Houghton Mifflin. This paper describes procedures for using these designs, In the current study, it is likely that exposure to some of the measures can affect scores on other measures or repeated exposure to a measure can lead to socially desirable responding or 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 non-concurrent multiple baseline across-individuals design: An extension of the traditional multiple baseline design. Therefore, researchers must exercise extreme caution in interpreting and generalizing the results from pre-experimental studies. B. Smith, J. D. (2012). Second, the across-tier comparison assumes that extraneous variables will affect multiple tiers similarly. https://doi.org/10.1177/0741932512452794, Lanovaz, M. J., & Turgeon, S. (2020). 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. Strategies and tactics of behavioral research. Further, for both types of multiple baselines, the threat of coincidental events should be evaluated primarily based on replicated within-tier comparisons. Google Scholar, Harvey, M. T., May, M. E., & Kennedy, C. H. (2004). Johnston, J. M., Pennypacker, H. S., & Green, G. (2010). This has been the topic of important recent methodological research, including studies of the interobserver reliability of expert judgements of changes seen in published multiple baseline designs (Wolfe et al., 2016) and use of simulated data to test Type I and II error rates when judgements of experimental control are made based on different numbers of tiers (Lanovaz & Turgeon, 2020). Consequently, it is often difficult or impossible to dismiss rival hypotheses or explanations. These variables share the key characteristic that their impact would be expected to accumulate as a function of number of experimental sessions. This raises the question of how many replications are necessary to establish internal validity. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The reversal model is fine for many questions, but in some instances, removing a type of treatment could be unwise or even unethical. 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. In a concurrent multiple baseline that involves a single participant across settings, behaviors, antecedent stimuli etc., this kind of event would be expected to contact all tiers. ), Single case research methodology: Applications in special education and behavioral sciences (pp. 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. the effects of the treatment variable are inferred from the untreated behaviors (p. 227). Journal of Consulting & Clinical Psychology, 49(2), 193211. https://doi.org/10.1901/jaba.1968.1-91, Article Adding multiple tiers to the design allows for two types of additional comparisons to be used to evaluate, and perhaps rule out, these threats: (1) replications of baseline-treatment comparisons within subsequent tiers (i.e., horizontal analysis), and (2) comparisons across tiers (i.e., vertical analysis). 66 : Discuss the advantages and disadvantages of using visual inspection of graphs rather than statistics to evaluate the significance of the results. Perspect Behav Sci 45, 647650 (2022). Watson and Workman described a nonconcurrent multiple baseline design in which participants could be begin a study as they became known to the researcher. WebExtended baselines or interventions may threaten experimental control, delayed intervention may pose a risk to client or others as an ethical concern. The Nonconcurrent Multiple-Baseline Design: It is What it 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. in their classic 1968 article that defined applied behavior analysis. 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. 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. These events would contact all tiers of a MB that take place in that single setting, but not tiers in other settings. Testing and session exposure may be particularly troublesome in a study that requires taking the participant to an unusual location and exposing them to unusual assessment situations in order to obtain baseline data. National Center for Biotechnology Information Likewise, setting-level coincidental events are those that contact a single setting. Routledge/Taylor & Francis Group. In this design, behavior is measured across either multiple individuals, behaviors, or settings. Journal of Consulting & Clinical Psychology, 49(2), 193211. The multiple baseline design is useful for interventions that are irreversible due to learning effects, and when treatment cant be withdrawn. In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. Behavioral cusps: A developmental and pragmatic concept for behavior analysis. Each replication requires an assumption of a separate event coinciding with a distinct phase change. (2020) make a somewhat different methodological criticism of nonconcurrent multiple baseline designs. Behavioral Interventions, 33(2), 160172. Chapter 14 quiz Wacker, D., Berg, W., Harding, J., & Cooper-Brown, L. (2004). The details of situations in which this across-tier comparison is valid for ruling out threats to internal validity are more complex than they may appear. Experimental and quasi-experimental designs of research. (1973). Later they present an overall evaluation of the strength of multiple baseline designs, attributing its primary weakness to its reliance on the across-tier comparison, The multiple baseline design is considerably weaker than the withdrawal design as the controlling effects of the treatment on each of the target behaviors is not directly demonstrated . https://doi.org/10.1007/s40614-022-00343-0, SI: Commentary on Slocum et al, Threats to Internal Validity. WebIn yet a third version of the multiple-baseline design, multiple baselines are established for the same participant but in different settings. However, as Hayes (1985) pointed out, even with the most rigorous care in experimental design, we can never give two individuals the same experiences outside of our experimental sessions. The general steps for the development of the line graphs are as follows: 1. If it changes at that point, evidence is accruing that the experimental variable is indeed effective, and that the prior change was not simply a matter of coincidence (p. 94). According to conventional wisdom, concurrent multiple baselines are superior because they allow for across-tier comparisons that can rule out coincidental events. Experimental and quasi-experimental designs for research. Routledge/Taylor & Francis Group. Kennedy, C.H. Some current dimensions of applied behavior analysis. They do not elaborate on the importance of this type of comparison. Webmultiple baseline (3 forms) 1. across bx 2. across settings, 3. across subjects or groups using 3-5 tiers. We use function of elapsed time descriptively rather than causally. The present article is focused on the second questionwhether systematic changes in data can be attributed to the treatment. 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 such an instance, there may be a disruption to experimental control in only one-tier of the design and not others, thus influencing the degree of internal In this article, we argue that the primary reliance on across-tier comparisons and the resulting deprecation of nonconcurrent designs are not well-justified. Identify the strengths and weaknesses of a multiple Describe the retrospective and prospective research designs. et al. Although it is plausible that an extraneous variables influence could coincide with one phase change, it is less plausible that such a coincidence would occur twice, and even less plausible that it would occur three times. Throughout this article we have referred to the importance of replicating within-tier comparisons, emphasizing the idea that tiers must be arranged with sufficient lag in phase changes so that specific threats to internal validity are logically ruled out. All three of these dimensions of lag are necessary to rigorously control for commonly recognized threats to internal validity and establish experimental control. 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. https://doi.org/10.1023/B:JOBE.0000044735.51022.5d, Hayes, S. C. (1981). So, similar to maturation, the across-tier comparison is sometimes able to reveal effects of testing and session experience, but it may fail to do so in some circumstances. As a result, concurrent and nonconcurrent designs are virtually identical in their control for maturation threats. write that after implementing the treatment in an initial tier, the experimenter perhaps notes little or no change in the other baselines (p. 94). The Family of Single-Case Experimental Designs The key characteristic that maturational processes share is that they may produce behavioral changes that would be expected to accumulate as a function of elapsed time in the absence of participation in research.Footnote 2 In order to control for maturation, we must attend to the passage of timetypically, calendar days. If A changes after B is put into practice, a researcher can draw the Conclusion that B caused A to change. 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. . PubMedGoogle Scholar. Article limitation of alternating treatment designs: o it is susceptible to multiple treatment interference, o rapid back-and-forth switching of treatments does not reflect the typical manner in which interventions are applied and may be viewed as artificial and undesirable. However, an across-tier comparison is not definitive because testing or session experience could affect the tiers differently. In addition, arranging tiers that are isolated in other dimensions (e.g., location, behaviors, participants) confers overall strength, not weakness, for addressing coincidental events. 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. Single-Subject Research Designs Research Methods in Longer lags and more isolated tiers can reduce the number of tiers necessary to render extraneous variables implausible explanations of results. 10.2 Single-Subject Research Designs Routledge. One is that if a https://doi.org/10.1007/s40614-022-00326-1, DOI: https://doi.org/10.1007/s40614-022-00326-1. For example, instrumentation is addressed primarily through observer training, calibration, and IOA. Therefore, concurrent and nonconcurrent designs are virtually identical in control for testing and session experience. To answer the first question, the one must distinguish signal (systematic change) from noise (unsystematic variance). Slocum, T.A., Pinkelman, S.E., Joslyn, P.R. Watson and Workman did not explicitly address threats to internal validity other than coincidental events. This certainty is increased by isolation of tiers in time and other dimensions. 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.