Description
Create a one page handout on the single-subject research designs. Please reference the rubric below. Be as creative as you like!List 3 strengths for each designsList 2 limitations for each designExplain when you would use each design (when it would be appropriate to use)Provide a sample graph of each design – you cannot use graphs from Richards or any other source; you must create the graphs and can use the ones you have created for assignments in this course Describe each design: Multiple-baseline, Reversal/Withdrawal, Changing Criterion, and Alternating Treatments
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Create a one page handout on the single-subject research designs. Please reference the rubric below. Be as creative as you like!
View Rubric
Partner Project – Handout
Handout Project
Criteria
Ratings
Pts
Description of each design Multiple baseline Reversal/withdrawal Changing criterion -Alternating
treatments
view longer description
4 pts
Full Marks
Full descriptions of each design provided
1 pts
Partial Credit
Full descriptions of at least 2 designs
0 pts
No Marks
Late or missing
/ 4 pts
Strengths of each design
view longer description
2 pts
Full Marks
At least 3 strengths listed for each design
1 pts
Partial Credit
1-2 strengths listed for each design
0 pts
No Marks
Late or missing
/ 2 pts
Limitations of each design
view longer description
2 pts
Full Marks
At least 2 limitations listed for each design
1 pts
Partial Credit
1 limitation listed for each design
0 pts
No Marks
/ 2 pts
Partner Project – Handout
Handout Project
Criteria
Ratings
Pts
Late or missing
Applications/when to use each
design
view longer description
Graph of each design
view longer description
Total Points: 0
2 pts
Full Marks
Identified when to use each design
1 pts
Partial Credit
Identified when to use 2-3 designs
0 pts
No Marks
Late or missing
/ 2 pts
20 pts
Full Marks
One sample graph is provided for each
design
10 pts
Partial Credit
One sample graph provided for 2 designs
0 pts
No Marks
Late or missing
/ 20 pts
Strengths
Limitations
Applications
Sample Graph
Multiple Baseline
Reversal/Withdrawal
Changing Criterion
Alternating Treatments
The above is a sample template that you and your partner can use to create the handout. You may also be creative and create a
different style handout. The only requirement is that it is a one page document.
Rubric for Handout – Partner Project
(30 points)
Description of each
design
-Multiple baseline
-Reversal/withdrawal
-Changing criterion
-Alternating treatments
Full Credit
Partial Credit
No Credit
Full descriptions of
each design
provided
Full descriptions of at
least 2 designs
Late or missing
1 point
4 points
Strengths of each design
Limitations of each
design
Applications/when to
use each design
Graph of each design
At least 3 strengths
listed for each
design
1-2 strengths listed for
each design
2 points
1 point
At least 2
limitations listed
for each design
1 limitation listed for
each design
2 points
1 point
Identified when to
use each design
Identified when to use 23 designs
2 points
1 point
One sample graph
is provided for
each design
One sample graph
provided for 2 designs
20 points
10 points
Late or missing
Late or missing
Late or missing
Late or missing
Chapter 10
Analyzing Results
from Single Subject
Studies
© 2019 Cengage. All rights reserved.
Learning Objectives
•
•
•
•
•
10-1 Describe and apply principles of visual analysis,
including when to use visual analysis and applying
visual analysis with and across phases.
10-2 Describe the advantages and disadvantages of
visual analysis.
10-3 Describe when and how to use statistical analysis,
and distinguish among statistical procedures.
10-4 Describe when and how to use qualitative
analysis.
10-5 Describe the advantages and disadvantages of
qualitative analysis.
© 2019 Cengage. All rights reserved.
10-1 Visual Analysis (1 of 3)
Visual Analysis of Data
•
•
•
Researchers involved in applied research and practice
frequently use visual analysis to make inferences about
behavioral changes
Visual analysis has limitations because of subjectivity that
may be involved
When to Use Visual Analysis – when continuous
numerical data are gathered, the data are graphically
depicted, and the researcher wishes to make formative and
summative analyses.
© 2019 Cengage. All rights reserved.
10-1 Visual Analysis (2 of 3)
•
Level of Behavior
–
The performance of the
target behavior and
where along the y-axis
the data points fall
▪
–
Should be depicted as
a jump in the data path
either upward or
downward
When the level changes
within phases, variability
is created and mean,
median, or range lines
may be needed to assist
in the visual analysis
© 2019 Cengage. All rights reserved.
Figure 10-2 Example Demonstrating Mean,
Median, and Range of Level of Performance
© 2019 Cengage. All rights reserved.
Figure 10-3 Example of the Split-Middle Method
for Determining Trend Lines
© 2019 Cengage. All rights reserved.
10-1 Visual Analysis (3 of 3)
•
An Immediate
Change in Level
– Assuming the
change is in the
desired direction,
immediate changes
may be indicative of
(but not prove) a
functional
relationship
© 2019 Cengage. All rights reserved.
10-2 Advantages and Disadvantages of
Visual Analysis
Advantages to Visual Analysis
• Relatively simple to use (assuming correctly scaled and accurate
graphic displays of data)
• Appears sufficient for revealing strong and robust intervention
effects that can literally be seen in many instances
• Can include descriptive statistical analyses that can assist in
visual inspection alone
• Requires that the researcher look beyond the numerical data and
consider outliers, unusual events, changes in level or trend, or
other variables that might have affected the outcomes of the
study
Disadvantages to Visual Analysis
• May be less reliable than statistical analysis
• Two analysts may not arrive at the same conclusions from visual
analysis (subjectivity)
© 2019 Cengage. All rights reserved.
10-3 Statistical Analysis (1 of 5)
•
When to Use Statistical Analysis
– When there is variability in baseline data but a trend is
evident
– When changes in trend across phases are difficult to
visually analyze
– When visual analysis does not establish a clear
intervention effect but one may be present
– When applied research typically involves many
extraneous variables that may affect variability of
performance
© 2019 Cengage. All rights reserved.
10-3 Statistical Analysis (2 of 5)
•
How to Use Statistical Analysis
– Descriptive and inferential statistics may be used
– Inferential statistics may be divided into parametric (e.g.,
t test, ANOVA) and nonparametric (e.g., randomization
test) procedures
– Parametric procedures have more rigorous assumptions
to be met for their use
© 2019 Cengage. All rights reserved.
10-3 Statistical Analysis (3 of 5)
•
Statistical Procedures
– Two general types of statistical procedures used by
researchers:
▪
▪
Descriptive measures (e.g., mean, median, mode,
frequency) are used to describe aspects of the data
without inferences to their statistical significance
Inferential statistics are used when the researcher wishes
to generalize her or his findings to other individuals (or
samples/populations)
© 2019 Cengage. All rights reserved.
10-3 Statistical Analysis (4 of 5)
•
Time Series Analysis
– A nonparametric
procedure that may be
more appropriate than
parametric procedures
but requires a large
number of
observations and is
somewhat complicated
for the novice
▪
Requires 20–100
data points in each
phase
© 2019 Cengage. All rights reserved.
10-3 Statistical Analysis (5 of 5)
•
Disadvantages to Statistical Analysis
– Assumptions for use may be violated
– Results may not indicate educational or clinical
significance
– Generally require knowledge and use of statistical
computer packages
© 2019 Cengage. All rights reserved.
10-4 Qualitative Analysis (1 of 5)
•
•
Research that has as its primary purpose the
determination of relationships, effects, and causes that
focus on individual variables
Qualitative analyses may involve case studies,
personal experiences, introspection, life stories,
interviews, and observational, historical, and/or visual
texts
© 2019 Cengage. All rights reserved.
10-4 Qualitative Analysis (2 of 5)
•
•
•
Interpretivist approach in which the researcher typically
attempts to tell the story of the study through the
collection of data and the examination of variables that
often are not quantitative
Mixed methods are increasing in popularity
When to Use Qualitative Analysis
– Qualitative methods may be used in virtually any study
so long as the researcher has identified some
variables/methods a priori and is flexible enough to
identify others as the study progresses
– Used as a supplement to either or both visual and
statistical analyses
© 2019 Cengage. All rights reserved.
10-4 Qualitative Analysis (3 of 5)
Combining Both Qualitative and Quantitative Research
1. Qualitative principles would be violated if the researcher spent
too little time observing
2. The researcher should maintain field notes
▪ Personal interpretation of the events is important in qualitative
research
3. The researcher must be involved in the study and be familiar with
the individuals who are subjects, those who may be involved in
collecting data, and applying the treatment variable, and those
whose lives may be affected by the outcomes (e.g., family
members)
4. The researcher must be prepared to collect data on variables that
become important as the study evolves
5. The researcher should interpret what is seen and heard
6. Biases related to the study should be acknowledged
© 2019 Cengage. All rights reserved.
10-4 Qualitative Analysis (5 of 5)
•
How to Use Qualitative Analysis
– Typically, field notes and observations are made,
compiled, analyzed, and presented by the researcher
– Mixing both qualitative and quantitative methods
– Also, it is essential to understand that while the
interpretations of the research by the researcher are
important, the interpretations of the research outcomes
by other participants including the subject(s) are often
equally important
© 2019 Cengage. All rights reserved.
10-5 Advantages and Disadvantages of
Qualitative Analysis
•
Advantages
– Provides interpretation by the researcher, but also by the
participants
– Researcher is able to more fully develop and explain the
data and events of the study
•
Disadvantages
–
–
–
–
Time demands may be greater
May require extensions of phases that are inappropriate
Resources needed may be scarce
Funding agencies may be less enthusiastic toward
qualitative approaches than quantitative approaches
– Reader should study these procedures further
© 2019 Cengage. All rights reserved.
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