Single-CaseDesigns
Single-Case Designs AKA single-subject, within subject, intra-subject design
Footnote on p. 163
Not because only one participant (although might sometimes) Because participant serves as his own control Each participant’s data are graphed and analyzed separately
“Case” doesn’t mean case study Case study is usually a narrative report of intervention with a
client and description of his behavior Sometimes data are provided, but no experimental control
Single-case design strategies…
Baseline Collecting data on the target behavior without your IV
May still have a treatment, but not your IV Sometimes the preferred item (used as reinforcer in tx) is
delivered contingent upon on-task/attending behaviors Why collect baseline data?
To compare it to and see effects of your intervention To determine the dimensions of the behavior: topography,
duration, frequency, latency, magnitude Get data on common antecedents and consequences to help
with designing an intervention for a problem behavior To get info on what the criteria for reinforcement should be
Notation:A = baselineB = IV #1C = IV #2D =
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Cummings and Carr (2005)
How Long Do You Collect Data in Baseline?
At least 3 data points to demonstrate a pattern of behavior 5 - 7 is better (Gina Green says a minimum of 6!)
Obtain a steady state (“get stability”) Little variability over time Steady state strategy: repeatedly exposing a participant to a given condition to
eliminate or control extraneous influences on behavior Your goal is to show the natural characteristics of behavior so that the effect of
treatment will be clear Stability is defined different ways – for a study you’re conducting, look at the lit in
that area and use that Mastery criterion: x sessions at or above 90% correct Visual inspection: Certain # of data pts with no trend or trend in opp direction
with little variability Statistical method: mean of last 3 data pts differs by less than x% from the
mean of the preceding 3 data pts Collection of BL data will show any practice effects 4 Baseline Patterns…
Review… Trend
Overall direction taken by the data path Trends can be increasing, decreasing, or no trend (flat) Draw a trend line with your eyes that represents the direction (up,
down, flat) that leaves about half of data pts below it and half above it. Compare direction and how steep
Level Value on y axis around which a set of data points converge Draw a straight horizontal line with your eyes that leaves
approximately half of the data points above it and half below Variability
Degree to which data points deviate from the overall trend
Stable Baseline No upward or downward trend Not much variability Allows you to clearly determine effects of your IV
Any changes in trend, variability, or level that happen when you start your tx can be more reasonable attributed to the tx
Ascending Baseline Increasing trend Behavior was in the process of changing during baseline! If your goal was to increase behavior in tx…
If you started treatment while behavior was increasing, could you tell if your tx had an effect?
If your goal was to decrease behavior in tx… If you have to start treatment, you can – why?
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Variable Baseline “Something” is having an effect on behavior
If you start your tx, that “something” could be affecting behavior during your tx
Try to figure out what’s producing the variability Control it If you can’t , demonstrate that variability is the natural state of the behavior
– ex: stereotypy
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• Behavior is observed repeatedly across time
Shows that the sample of behavior being measured is representative of that student
Shows pattern of behavior over time
Why is it important to measure behavior repeatedly?
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Repeated Measures
Baseline Treatment
Prediction Anticipated outcome of future measurement Without the IV…
Trend, level, and variability would be the same as it has been
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Baseline
Affirmation of the Consequent Logic used in single-case designs to demonstrate a functional
relationship between IV and DV If the IV were not implemented, the behavior would not change When the IV is implemented, the behavior changes
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Verification
Demonstrating that prior baseline responding would have remain unchanged if the IV hadn’t be implemented
Verifies your prediction Reduces the possibility that something besides your IV was responsible for
the change in your DV!
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Replication
Repeating IV manipulations conducted previously in the study and obtaining similar outcomes
Same participant: Intrasubject direct replication Different participant in same study: Intersubject direct replication
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Types of Single-Case Designs
A-B Reversal Alternating Treatments Multiple Baseline Changing Criterion
Effects of a new medication on outbursts
Was the medication effective for Joe?
“B” Design
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A-B Design
Baseline phase followed by a treatment phase
An effect is demonstrated by showing that behavior changes from one phase to the next
A-B Design
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Was the token system effective?
Effects of a token system on number of correct math problems
A-B Design: Advantages and Disadvantages
Advantages: simple, brief, no reversal Disadvantage - changes in behavior may be the
result of something besides your treatment No verification or replication to show that it was
the IV that caused the change in the DV Can’t demonstrate experimental control Considered a “quasi-experimental design” Main threats to internal validity
History Maturation
Used clinically and with self-management projects
Watson and Sterling (2005)
A-B Design: Review
• Does the design allow us to see a change in DV (without regard to whether it was caused by the IV)? YES
• Does the design allow us to infer a functional relationship between IV and DV? NO
• What threats to internal validity (confounds) does the design control for? NONE