The consensus in recent textbooks and methodological papers is that nonconcurrent designs are less rigorous than concurrent designs because of their presumed limited ability to address the threat of coincidental events (i.e., history). This is a significant problem for the across-tier comparison because its logic is dependent on these two assumptions. Pearson Education. In a review of the SCD literature, Shadish and Sullivan (2011) found multiple baseline designs making up 79% of the SCD literature (54% multiple baseline alone, 25% mixed/combined designs). All three of these dimensions of lag are necessary to rigorously control for commonly recognized threats to internal validity and establish experimental control. In this case, the effects of this kind of event could be revealed through the across-tier comparison of participants or behaviors that have not been exposed to the independent variable. The replicated within-tier analysis looks to patterns of results within the other tiers. This raises the question of how many replications are necessary to establish internal validity. A study may be at heightened risk of coincidental events if the target behavior is particularly sensitive to events in the environment that are uncontrolled by the experimenter. Nonconcurrent multiple baseline designs and the evaluation of educational systems. https://doi.org/10.1002/bin.191, Article Second, we briefly summarize historical methodological writing and current textbook treatment of these designs. For example, instrumentation is addressed primarily through observer training, calibration, and IOA. a potential treatment effect in the first tier would be vulnerable to the threat that the changes in data could be a result of Webmultiple baseline (3 forms) 1. across bx 2. across settings, 3. across subjects or groups using 3-5 tiers. AB Design. WebDisadvantage: Covariance among subjects may emerge if individuals learn vicariously through the experiences of other subjects Also, identifying multiple subjects in the same PubMedGoogle Scholar. (2011). https://doi.org/10.3758/s13428-011-0111-y, Article He acknowledged that earlier authors had stated that multiple baselines must be concurrent and he noted that in a nonconcurrent multiple baseline the across-tier comparison could not reveal coincidental events. The assumption that all tiers respond similarly to maturation may be somewhat more problematic. Events that contact a single participant may be termed participant-level. WebNew Mexico's Flagship University | The University of New Mexico To understand the ability of concurrent designs to meet these assumptions we must distinguish different types of coincidental events based on the scope of their effects. For example, in a multiple baseline across participants, all the residents of a group home may contact peanut butter and jelly sandwiches for lunch but this change may disrupt the behavior of residents with a mild peanut allergy, but not other residents. Perspectives on Behavior Science 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. Although many maturational changes are gradual, more sudden changes are possible. Having identified the criticisms of nonconcurrent multiple baseline designs, we now turn to a detailed analysis of threats to internal validity and features that can control these threats. Neither the within-tier comparison, nor the across-tier comparison depends on the tiers being conducted simultaneously; both types of comparisons only require that phase changes occur after substantially different amounts of time since the beginning of baselinethat is, each tier is exposed to different amounts of maturation (i.e., days) prior to the phase change. Nonconcurrent multiple baseline designs are those in which tiers are not synchronized in real time. 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. the effects of the treatment variable are inferred from the untreated behaviors (p. 227). Oxford. Coincidental events (i.e., history) are specific events that occur at a particular time (or across a particular period) and could cause changes in behavior. Application of multiple baseline designs in behavior analytic research: Evidence for the influence of new guidelines. Poor execution can certainly worsen these problems, but good execution cannot eliminate them. In the case of multiple baseline designs, a stable baseline supports a strong prediction that the data path would continue on the same trajectory in the absence of an effective treatment; these predictions are said to be verified by observing no change in trajectories of data in other tiers that are not subjected to treatment; and replication is demonstrated when a treatment effect is seen in multiple tiers. Multiple baseline and multiple probe designs. If session experience exerted a small degree of influence on the DV, an effect might be observed in settings where the behavior is more likely, but not in settings where the behavior is less likely. There is ample empirical evidence of differential impact of variables across tiers. The strength of this control is a function of our certainty that no single coincidental event could have caused more than one change in the dependent variable. This pattern seriously weakens the argument that the independent variable was responsible for the change in the treated tier. Rosales-Ruiz, J., & Baer, D. M. (1997). When conditions are less ideal, additional tiers may be necessary. One area that has, in the past, been particularly controversial is the experimental rigor of concurrent versus nonconcurrent multiple baseline designs; that is, the degree to which each can rule out threats to internal validity. Single-case experimental designs: A systematic review of published research and current standards. Throughout this article we have argued that controlling for the three main threats to internal validitymaturation, testing and session experience, and coincidental eventsin multiple baseline designs requires attention to three distinct dimensions of lag of phase changes across tiers. Remedial and Special Education, 34(1), 2638. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Peer reviewers and editors who serve as gatekeepers for the scientific literature must also have a deep understanding of these issues so that they can distinguish between stronger and weaker research, ensure that information critical to evaluating internal validity is included in research reports, and assess the appropriateness of discussion and interpretation of results. In order to demonstrate experimental control, the researcher makes two paradoxical assumptions. 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 . As Kazdin and Kopel point out, it is clearly possible for treatments to have broad effects on multiple tiers and for extraneous variables to have narrow effects on a specific tier. Textbooks commonly describe and characterize the design without clearly defining it. Features of the target behaviors, participants, measurement, and so forth can make threats to internal validity more or less likely. Other threats to internal validity such as (1) ambiguous temporal precedence, (2) selection, (3) regression, (4) attrition, and (5) instrumentation are addressed primarily through other design features. WebIn yet a third version of the multiple-baseline design, multiple baselines are established for the same participant but in different 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. In both within- and across-tier comparisons, the dates on which the sessions took place are not relevant to the effects of testing and session experience. https://doi.org/10.1007/s40614-022-00343-0, SI: Commentary on Slocum et al, Threats to Internal Validity. It is possible that a coincidental event may be present for all tiers but have different effects on different tiers. write that after implementing the treatment in an initial tier, the experimenter perhaps notes little or no change in the other baselines (p. 94). We use function of elapsed time descriptively rather than causally. Thus, the assumption that the coincidental event contacts all tiers would be valid and the across-tier analysis might reveal the effects of this sort of event. Hersen, M., & Barlow, D. H. (1976). PubMed For example, knowing the date of session 10 in tier 1 tells us nothing about the date of session 10 in tier 2. Kazdin and Kopel (1975) parallel much of Hersen and Barlows (1976) commentaryFootnote 3 but they also point out an apparent contradiction in the assumptions about behavior on which the multiple baseline design is built. Ten sessions of baseline would be expected to have similar effects whether they occur in January or June. Single case experimental designs: Strategies for studying behavior change (3rd ed.). Type I Errors and Power in Multiple Baseline Designs, Assessing consistency of effects when applying multilevel models to single-case data. As a result, concurrent and nonconcurrent designs are virtually identical in their control for maturation threats. WebDisadvantages to Multiple Baseline Designs -Weaker method of showing experimental control than a reversal (b/c no withdrawal of treatment) -Delay in treatment can occur as Learn more about Institutional subscriptions. WebMultiple-Baseline Designs There are two potential problems with the reversal designboth of which have to do with the removal of the treatment. Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide. 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). Although publication dates would suggest that Kazdin and Kopel (1975) was published before Hersen and Barlow (1976), Kazdin and Kopel cite Hersen and Barlow, and not the other way around. Using Single-Case Designs in Practical Settings: Is Within-Subject Replication Always Necessary? WebA multiple baseline design across behaviors was used to examine intervention effects. Perspectives on Behavior Science, 43, 605616. Journal of Behavioral Education, 13(4), 213226. Two articles published in 1981 described and advocated the use of nonconcurrent multiple baseline designs (Hayes, 1981; Watson & Workman, 1981). 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). 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. 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. Applied behavior analysis (3rd ed.). On the other hand, if we see a change in a treated tier and no change in untreated tiers, does this constitute strong evidence to rule out threats to internal validity? A researcher who puts great confidence in the across-tier comparison could falsely reject the idea that coincidental events were the cause of observed effects. WebExtended baselines or interventions may threaten experimental control, delayed intervention may pose a risk to client or others as an ethical concern. Coincidental events might be expected to be more variable in their effect than interventions that are designed to have consistent effects. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). The author has no known conflicts of interest to disclose. However, an across-tier comparison is not definitive because testing or session experience could affect the tiers differently. One is that if a First, the design assumes that treatment effects will be tier-specific and not spread to untreated tiers. 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. If a potential treatment effect is seen in one tier and on the same day there is no change in other tiers, this is taken as strong evidence that the potential treatment effect was not a result of a coincidental event, because a coincidental event would have had an effect on all tiers. 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. Single-case experimental designs: Strategies for studying behavior change. https://doi.org/10.1023/B:JOBE.0000044735.51022.5d, Hayes, S. C. (1981). Single-case designs for educational research. The ABA or Reversal Design PubMed Central Nonconcurrent multiple baseline designs for educational program evaluation. 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 Google Scholar. Routledge/Taylor & Francis Group. Recommendations for reporting multiple-baseline designs across participants. Additional replications further reduce the plausibility of extraneous variables causing change at approximately the same time that the independent variable is applied to each tier. in their classic 1968 article that defined applied behavior analysis. This comparison may reveal a likely maturation effect. . They do not mention the across-tier comparison, presumably because they believe that this analysis is not necessary to establish experimental control. 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. Craig H. Kennedy. Book The authors discuss two designs commonly used to demonstrate reliable control of an important behavior change (p. 94). 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. This critical requirement is mainly addressed by the lag between phase changes in successive phases. Threats to Internal Validity in Multiple-Baseline Design Variations. 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. 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. 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. The lag between phase changes must be long enough that maturation over any single amount of time cannot explain the results in multiple tiers. volume45,pages 619638 (2022)Cite this article. Smith, J. D. (2012). To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. This certainty is increased by isolation of tiers in time and other dimensions. Concurrent multiple baseline designs are multiple baseline designs in which the tiers are synchronized in real time. Pergamon. In this article, we first define multiple baseline designs, describe common threats to internal validity, and delineate the two bases for controlling these threats. They state, the nonconcurrent multiple baseline across participants design is inherently weaker than other multiple baseline design variations. 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. However, it does not rule out maturation as an alternative explanation of the change in behavior. 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. 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. Wacker, D., Berg, W., Harding, J., & Cooper-Brown, L. (2004). On resolving ambiguities of the multiple-baseline design: Problems and recommendations. By nature, undetected events are unknown. The across-tier comparison of concurrent multiple baseline designs is less certain and definitive than it may appear. Alternating Treatment Designs Watch on What are the disadvantages of alternating treatments?
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