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Single subjects research


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Single subjects research

  2. 2. DEFINITION • A research of collecting data from a few individual. For example: researcher who wish to study children who suffer from multiple disability for example who are both deaf and blind may have only a small number of children available to them. • Number of available is six or less. It would make little sense to form two groups of three each in such an instance. • Each child would probably need to be observed in great detail.
  3. 3. SINGLE SUBJECT DESIGN • Adaptations of the basic time-series design shown the previous chapter . • Data are collected and analyzed for only one subject at a time. • Commonly used to study the changes in behavior an individual exhibits to an exposure to an intervention or treatment of some sort.
  4. 4. CHARACTERISTIC The Graphing Of Single-Subject Design • Primarily use line graphs to present their data and to illustrate the effects of a particular intervention or treatment. • Vertical axis usually display the dependent (outcome) variable. • Horizontal axis used to indicates sequence of time.
  5. 5. • Figure 14.1 presents an illustration of such a graph. The dependent (outcome) variable is displayed on the vertical axis (the ordinate, or y-axis). • The horizontal axis (the abscissa, or x-axis) is used to indicates sequence of time, such as sessions, days, week, trials or months.
  6. 6.  The A-B Design • The basic approach of researchers using an A-B design is to collect data on the same subject, operating as his or her own control, under two conditions or phases. • The first condition is the pretreatment condition called baseline period is identified as A. The baseline is extremely important in single-subject research since it is the best estimate of what would have occurred if the intervention were not applied. • Once the baseline condition has been established, a treatment or intervention condition, identified as B.
  7. 7. Figure 14.2 A-B Design As you can see, five measures were taken before the intervention and five more during the intervention. Looking at the data in figure 14.2, the intervention appears to have been effective. The amount of responsiveness after the intervention increased markedly.
  8. 8. The A-B-A Design A-B-A design will able researcher to simply adding another baseline period. This may improves the design considerably.
  9. 9.  The A-B-A-B Design • Two baseline period are combined with two treatment periods. • This further strengthens any conclusion about the effectiveness of the treatment. • It permits the effectiveness of the treatment to be demonstrated twice. • In fact, the second treatment can be extended indefinitely if a researcher so desires.
  10. 10.  The B-A-B Design • In such cases, a B-A-B design may be used which involves a treatment followed by a baseline and also followed by a return to the treatment. • It usually according to times when an individual’s behaviour is so severe or disturbing.
  11. 11.  The A-B-C-B Design • A further modification of the A-B-A design. • C refers to a variation of the intervention in the B condition. • In the first two condition, the baseline and intervention data are collected. • During the C condition, the intervention is changed to control for any extra attention the subject may have received during the B phase. • The C condition, therefore, might be praise given no matter how the subject responds.
  12. 12.  Multiple-Baseline Design • Alternative for A-B-A-B design • Used when it is not possible or ethical to withdraw a treatment and return to the baseline condition. • When using this design, researchers do more than collect data on one behavior for one subject in one setting. • They collect on several behaviors for one subject, obtaining a baseline for each during the same period of time.
  13. 13. Threat to Internal Validity in SingleSubject Research It involve the :  The length of the baseline and intervention conditions  The Number of Variables Changed When Moving from One Condition to Another  The Degree and Speed of Change  The Return to Baseline Level  Independence of Behaviour  Number of Baselines
  14. 14. CONDITION LENGTH  Refers to how long the baseline and intervention conditions are in effect.  The number of data points gathered during a conditions.  Minimum three of data point to establish a clear pattern or trend.  As a hypothesis,in a certain period or condition of length,the researcher need to gathered enough data as it will establish the clear pattern
  15. 15.  Figure 14.10 (a)  Figure 14.10 (b)
  16. 16.  NUMBER OF VARIABLES CHANGED WHEN MOVING FROM ONE CONDITION TO ANOTHER  Only one variable should be changed at a time when moving from one condition to another  When analyzing a single – subject design,it always important to determined whether only one variable at a time has been changed
  17. 17. DEGREE AND SPEED OF CHANGE  In single-subject research,the stability is important  The data change at the time the intervention condition is implemented influenced the stability of baseline (when the independent variable is introduced or removed)
  18. 18.  Figure 14.11(a)  Figure 14.11(b)
  19. 19.  Figure 14.11(c)
  20. 20. RETURN TO BASELINE LEVEL  The subject’s behaviour did not return to the original baseline level suggest that the one or more extraneous variable may have produced the effects observed during the intervention condition
  21. 21. Differences in Return to Baseline Conditions  Figure 14.12(a)  Figure 14.12(b)
  22. 22. NUMBER OF BASELINES  In order to have a multiple – baseline design,researcher must have at least two based line  Baseline begin at same time,the intervention occur in different time  More baseline and intervention will lead to invalid conclusion
  23. 23.  NUMBER OF BASELINES  The greater number of baselines,the greater the probability that the intervention is the cause of any change in behaviour  The more baselines,there are,the longer the later behaviours must remain in baseline  The fewer the number of baseline,the less likely we can conclude that is the intervention rather than some other variable that causes any change in behaviour
  24. 24.  CONTROL OF THREATS TO INTERNAL VALIDITY IN SINGLE-SUBJECT RESEARCH Single-Subject designs are most effective in controlling for :  Subject characteristics  Mortality  Testing  History
  25. 25. EXTERNAL VALIDITY IN SINGLE-SUBJECT RESEARCH:THE IMPORTANCE OF REPLICATION  Single subject studies are weak when it comes to external validity  Total rely on replicationsacross individual instead of groups  The result worthly of generalization