Title: Multiple Baseline Designs
1Multiple Baseline Designs
- Chapter 7
- Single Subject Research and Design
2Multiple Baseline
- Description
- Multiple measures are used to obtain data over
two or more baselines - The end result appears visually as a series of
A-B designs on top of one another - The DV may consist of 2 or more different
behaviors - Versatile and relatively easy to understand
- Perhaps the most common design in use today
3Multiple Baseline Design
- If 3 dependent variables have been chosen,
baseline data is obtained for all three dependent
variables - The researcher implements the intervention for
the first DV while maintaining baseline
conditions for the other two - When the criterion is obtained on the first
behavior, the intervention may be implemented and
analyzed as to its effect on the second DV - A follow-up stage is included to ensure that the
effects of the IV are maintained
4Multiple Baseline Design
- MBD are used
- When withdrawal or reversal designs may not be
feasible due to ethical concerns of withdrawing
treatment - When practical considerations are necessary, such
as more than one person needing interventions - In cases where the IV should not be withdrawn or
the achieved target behavior cannot be reversed
5Prediction Verification and Replication
- Verification is evident if the data path changes
in a predictable manner through a phase change,
as from baseline to intervention - Inferences can be made concerning the
complimentary roles of prediction and
verification - 1. If potential confounding variables are held
constant across all variables and the target
behavior remains unchanged from DV 1 to variables
2 and 3, then the prediction is valid - 2. if changes in the IV occur with DV 1, the
observed changes in the target behavior are
brought about by the IV because only that DV was
exposed to the IV
6Replication
- Replication is achieved when similar results are
obtained with each DV following the introduction
of the same IV - Replication can provide evidence of a functional
relationship between the dependent and
independent variables
7Covariance Among Dependent Variables
- The variables in the treatment may covary, so it
is important to select dependent variables that
exhibit some degree of independence - Each dependent variable must be measured using
the same method of recording behavior
8Advantages of Multiple Baseline Designs
- The withdrawal of an effective treatment is not
required to demonstrate the functional
relationship between the IV and DV - The sequential implementation of the IV parallels
the practice of teachers - Generalization of behavior change is monitored
through the design - The design is easily used and conceptualized
9Disadvantages of Multiple Baseline Design
- Possibility of covariance
- Functional relationships may not be clearly
demonstrated - Verification relies on the dependent variable
levels not changing until the independent
variable is introduced and then changing in a
similar manner to any previously treated
behaviors - Implementation can be time consuming and may
require substantial resources
10Multiple Baseline design should not be used
- When selected target behaviors are not
functionally similar nor independent of one
another - If there is only one subject in one setting and
one target behavior - When more than one intervention phase is
desirable to demonstrate the functional
relationship - When constraints on resources make implementation
impossible
11Multiple Baseline Across Behavior
- Three or more behaviors are identified that are
exhibited by the same subject in the same setting
and then systematically subjected to the same
intervention or independent variable
12Critical Issues in Implementing a MB Across
Behaviors Design
- 1. selection of an individual participant who
displays multiple behaviors in a single setting
that require intervention - 2. functional similarity and independence of
those behaviors as one might be able to determine
priority - 3. a reasonable expectation that the same
variables will exert equal influence on each of
the dependent variables
13Critical Issues (continued)
- 4. selection of a treatment that can be expected
to produce a similar and independent effect on
each of the dependent variables - 5. a consistent recording procedure for each of
the target behaviors and a criterion level for
decision making - 6. confidence that the resources and time needed
to record multiple baselines and subsequent
intervention will be maintained throughout the
study
14Multiple Baseline Across Settings
- Only one subject is identified but the researcher
identifies two or more settings in which the
individual emits the same behavior - The same subject is treated for the same behavior
in different settings
15Issues in the Implementation of the MB Across
Settings design
- 1.Selection of an individual subject who displays
the same target behavior in multiple settings - 2. selection of settings that are functionally
similar but also independent of one another as
one may best determine priority - 3. a reasonable expectation that the same
variables will be exerting the same influence in
each of the settings
16Issues continued
- 4. selection of a treatment that can be expected
to produce similar effects in each setting - 5. a consistent recording procedure for each
setting and a criterion level for decision making - 6. confidence that resources will be maintained
throughout the length of the study
17- It is important to note that a major disadvantage
of MB across settings design is that extraneous
variables that may influence responding in
different settings can be difficult to control or
predict.
18Multiple Baseline Across Subjects
- In this design more than one subject
participates. - Two or more individuals are identified that emit
the same target behavior in the same setting - The subjects should be enough alike that one can
expect each subject to respond similarly to the
same intervention yet independent enough of one
another to avoid covariance
19Issues in Implementing a MB across Subjects Design
- 1. selection of individual participants who
display the same target behavior in the same
setting - 2. The subjects should be enough alike that one
can expect each subject to respond similarly to
the same intervention yet independent enough of
one another to avoid covariance - 3. a reasonable expectation that the same
variables will exert the same influence on each
of the subjects
20Issues in Implementing a MB across Subjects Design
- 4. selection of an independent variable that is
likely to have a similar effect on each subject - 5. a consistent recording procedure for each of
the target behaviors and a criterion level for
decision making - 6. confidence that the resources and time needed
to record multiple baselines and subsequent
intervention will be maintained throughout the
study
21Adaptations of the Multiple Baseline Design
- Multiple Probe Design
- Data probes are taken during baselines rather
than continuous measurement - Used to decrease the collection of data
- Researcher makes periodic recordings (probes) of
baseline levels to ensure that no significant
changes have occurred before the introduction of
the intervention - The use of probes reduce the need for resources
that may be unavailable to maintain the
continuous recording of behavior during baseline
phases
22- Delayed Multiple Baseline Design
- May be employed when a withdrawal design no
longer is possible or when other behaviors,
settings, or individuals emerge that are in need
of intervention - Baselines are not measured at the same time
- It allows the use of fewer resources and the
researcher may extend the study to new
behaviors, settings, and individuals that had not
been targeted a priori