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  • 1. Graduate Research and Statistics Lab
    CEDP 524
  • 2. Single Subject (small n)
    Problems with group analysis
    Individual differences are ignored
    These are important factors!
    This logic is based on farming analysis!
    The logic of single subject is high levels of internal validity (control) then replication.
    Systematic,
    Direct
  • 3. Experimental Single Subject Design
    Using a subject as their own control
    If we establish a pattern of responding and then change that pattern of responding at the exact moment the IV is present we conclude that it was the IV that had the effect
  • 4. Reversal design
    Shifting conditions – must be something that is not a permanent change
    Baseline (Stability)
    Treatment (stability)
    Baseline (stability)
    Treatment (stability)
    ABA designs, ABAB designs, ABAC
    Showing effects across people
    Ethics
  • 5. Multiple Baseline
    Several individuals
    Baselines overlap to control for environmental variables.
    The treatment is then introduced at different times for each
    If the behavior changes in each person at the treatment time, then the IV has the effect.
  • 6. Changing criterion
    Modify the criteria as it is reached until a given level is desired
    Step down/up approach
  • 7. Quasi Experimentation
    Internal vs. external validity
    Internal allows you to detect effects
    But is generally low in applicability
    External validity makes the study applicable
    But decreases chance to detect effect.
  • 8. Archival studies
    Looking at events in history and measuring their effect
    Looking at records
    Looking at changes before and after.
    No ability to detect cause.
    Naturalistic observations combined with sound data collection.
  • 9. Time series design
    Repeated measures
    Time one and time two are the minimum
    Can be an experimental treatment
    Pre M X post M
    Single group pre-post design.
    Remember – no control here – so cannot truly conclude if the X made the changes.
  • 10. Interrupted time series
    Adding more pre and post tests
    Allows us to assess changes that we cant see with a single shot.
    M M M M X M M M M M
  • 11. Multiple time series
    Just like multiple but uses a control group!
    No random assignment though.
    Adds some control – but still cant detect cause
  • 12. Non-equiv before after design
    When your groups are different before the study starts.
    Or you expect they are!
    M X M
    M M
    Compare differences in terms of groups to themselves.
  • 13. Ex-post facto design
    Retrospective comparisons
    An early event – with a later event
    Participating in debate – becoming a leader
    Medical or behavior problems associated with later issues (heart disease)
    Identify group of interest (those serial killers)
    Look for patters using various predictors
    Compare to a selected control group
    Could be randomly chosen people from the year book
  • 14. Correlational designs
    Designs that are relating variables
    But not seeking to see which causes the other
    Used not to establish cause
    But to show a relationship to then allow for further study
    Prevents us from wasting time and resources
  • 15. Naturalistic study
    Simply observing and describing
    Darwin on the HMS Beagle
    Started as simple observations
    Went on to develop ideas
    Eventually a theory
    Now tests of that theory
    Now it exists as a definition of life.
    Hawthorne effect (reactance)
    Being observed causes changes
    Use unobtrustive observations
    Selective perception
    We choose to focus on certain things
    We are influenced by what we expect to see
    Boredom – leads you to looking for boredom!