Spring 2001
REHB 509B
Behavior Analysis Research Designs:
Group Experimental Designs
The syllabus is subject to error correction and minor change in content during the
course.
Instructor: Anthony J. Cuvo, Ph.D.
Rehn 311A
acuvo@siu.edu
Phone 536-7704; FAX (618) 453-8271
http://www.siu.edu/~rehabbat/Enhanced/faculty.html
Syllabus On-line: http://www.siu.edu/~rehabbat/Cuvo/Rhab509b.pdf
Time: 12:00-1:15 PM, Tuesday and Thursday
Classroom: Rehn 326
COURSE DESCRIPTION & GOALS:
The purpose of this course is to provide a foundation in applied research
methods pertinent to program evaluation, group experimental design, and related
data
analysis. After completing the course you should be able to do the following:
a) Be a knowledgeable consumer of group design and related statistical analysis
literature (i.e., understand and critically evaluate research in journal articles and
other
research presentations).
b) Have intermediate level skill generating group design studies, knowing which
data analysis techniques are appropriate, using a computer for basic statistical
analyses, and drawing appropriate conclusions.
Principal Text (available at local bookstores)
Christensen, L. B. (2001). Experimental Methodology (8th ed.). Boston: Allyn &
Bacon.
Huck, S. W., (2000). Reading statistics and research (3rd ed.). New York:
Addison Wesley Longman.
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Additional Required Readings
Additional readings are available from the Printing Plant, 606 S. Illinois Avenue.
These readings, indicated by asterisks in the syllabus, supplement and are
equally
important to those in the textbooks. Page through the entire reading packet as
soon as
you get it and compare it to the syllabus. If you find missing pages or pages that
are
not legible go to the Printing Plant and ask them to rectify the situation. You are
responsible for all assigned readings on the due date.
Requirements and Grading
1. There will be 4 tests @ 100 points each on: February 13, March 20, April 12,
May 9.
Tests will emphasize the material since the previous test; however, the content is
cumulative and you should be able to relate earlier concepts to the current
material on the
tests. Students must remain in the classroom until finished with the test. Take
care of any
personal needs before coming to the classroom.
Total possible: 400 points
2. There are 3 conceptual projects that require you to apply the material in this
course. The forms for the first two are available on-line at
http://www.siu.edu/~rehabbat/ExpDesignProj.doc. The form in is Microsoft Word
format
and can be downloaded on disk or to your computer. You will need to use Word
or a
program that will open Word. The form is the same one used in Rehab. 509A.
Although
projects 1 and 2 could be on the same general topic (e.g., child abuse,
biofeedback,
mental retardation), each must be on a different specific topic. Projects should
include a
new literature review and independent variable. Projects should not be just minor
variations of each other. About 90% of the points lost in past years have been
due to
not following APA style and not answering all components of the questions. Put
Projects in instructor's mailbox in Rehn 317 by 4:00 PM on the due date. Note
that
Rehn 317 will be locked promptly by 4:30 PM. The office also will be closed
between
12:00-1:00 PM. There will be a 33% per day reduction in the maximum point total
for
late assignments, including weekend days.
Project due dates and point values:
Project 1 (3/5/01) 20 points
Project 2 (4/2/01) 25 points
Project 3 (4/30/01) 10 points
Total possible: 55 points
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3. A 15 minute quiz will be given at the beginning of 22 classes indicated on the
syllabus. Each quiz will be worth 10 points. If you come to class while the quiz is
being
administered, you will have until time expires on the quiz to finish. If you come to
class
after the quiz has been completed, you will not have the opportunity to take it and
you
will receive a grade of 0 for that quiz. If you plan to be absent from class, it is
your
responsibility to arrange to take the scheduled quiz or test in advance of the
class you
will not attend.
Total possible: 220 points
Point to letter grade conversion:
A = 675-607 points
B = 606-540 points
C = 539-472 points
Lower grades are available on the same proportional scale.
If you have earned 90% of the points up to and including the first 18 quizzes, first
three tests, and the three projects (i.e., 481 points exactly, no rounding) and
made a
minimum score (not average) of 9 on each quiz in the last course unit, you will be
exempt from taking the final exam and receive an “A” in the course. The quiz
points for
the final unit are not included in the 90% criterion.
• If you are having difficulty with this material, see the professor as soon as
possible.
• If you wish to drop this course for any reason, the Graduate School has a final
date that you can do this. It is your responsibility to drop by the date designated
by
the Graduate School.
• A grade of Incomplete will be given only under the conditions specified in the
Graduate School Catalog.
The reading list includes a number of journal articles that present experimental
research. These articles serve as models for the integration of conceptual issues,
research questions, measurement procedures, experimental design, data
analysis, and
inferences from the data to past research and conceptual issues. You should
read
these articles and try to understand the integration of the various components of
the
research process; however, an article has been assigned for a particular class
because
it illustrates the topic for that class. Focus, in particular, on the aspect of the
article that
is related to the topic for that class.
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You will have three statistical projects to do in this course using a computer
and software of your choice. It is recommended that you identify the computer
and
software that you will use and gain familiarity with both before you start your first
project.
The readings and exercises from the Internet are no different from other
assigned readings with respect to their importance and availability for material for
quizzes and tests.
It is recommended that you take your readings to class, especially the ones
for that day.
A number of computer data analysis examples have been included in your
reading packet. They present a research question, design, computer data
analysis, and
interpretation. Various statistical packages have been used for these examples.
Try to
understand the research and data analysis, and don’t get bogged down in the
mechanics of how to use the software. You should try to understand the printouts
and
interpretation of results.
Try to do the readings in the sequence indicated on the syllabus.
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***January 16, 2001
Introduction to course
Video: Facilitated Communication
***January 18-23, 2001 (Science & Theory)
Readings:
1/18/01
"Much like the law of gravity, the laws of learning are always in effect.
Thus, the question is not whether to use the laws of learning, but rather
how to use them effectively." From "Learning Principles" (Spreat & Spreat)
The above quote is related to the goal of science, to discover the orderliness or
lawfulness in nature. Those lawful relations about human behavior always have
existed,
and they are there waiting for us to discover them. We discover them using
scientific
methods, and that discovery can lead to useful applications in human services.
This
course focuses on the role of certain aspects of scientific methodology as a tool
for
understanding variables that relate to human services.
These initial readings are a varied collection that have a common theme- the big
picture pertaining to research and program evaluation. They address
philosophical
issues, definition and characteristics of science, research questions, and
conceptual
issues. They address the larger issues that surround the more focused tactics of
research methodology.
Christensen Chap. 1
* Shermer, M. (1992). A skeptical manifesto. Skeptic, 1, 15-21. (This article
advocates a basic approach, a “mind-set” as some might say, to examine claims
about
causal events in the universe. Do you believe everything that people tell you?
How do
you decide what to believe? What is your criterion for truth?)
* Cuvo, A.J. Rational Skepticism and Research Methodology
* Green, G. (1996). Evaluating claims about treatments for autism. In C. Maurice,
G. Green. & S. C. Luce. (Eds.). Behavioral intervention for young children with
autism
(pp. 15-28). Austin: Pro-Ed.
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1/23/01
Christensen, Chaps. 3 & 4
* Cuvo, A. J. How to Ask Research Questions or Words Mean Something
* Exploring psychology scientifically-Asking testable questions
http://gateway1.gmcc.ab.ca/~digdonn/psych104/think.htm (Download from
Internet.
Test yourself with this exercise.)
* Riggin, L.J.C. (1990). Linking program theory and social science research. In
L. Bickman (Ed.), New directions for program evaluation: Advances in program
theory,
no. 47 (pp. 109-120). San-Francisco: Jossey-Bass. (This article makes a point
similar to
that made by Cuvo above. It shows not only that human service programs should
have
a theory on which the program delivered to clients is based, but also the program
theory
should be evaluated in light of the manner in which the program actually is
delivered. Is
the program as conceptualized on paper, congruent with the program in
operation?
Does the program theory have to be revised to reflect reality?)
QUIZ 1 1/23 only, based on readings for both dates. No quiz on 1/18
***January 25-30, 2001 (Variables Used in Experimentation; Measurement
Principles and Applications)
Readings:
1/25/01
You might want to read pp. 101-105 from Meltzoff and then the pages from
Christensen on the independent variable first, and then the remaining of the
Meltzoff
and Christensen chapters on the dependent variable.
Christensen Chap. 6
* Cuvo, A. J. Independent Variables and Conceptual Models
*Meltzoff, J. (1998). Chap. 7 Criteria and criteria measures. In Critical Thinking
About Research. APA: Washington.
QUIZ 2
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1/30/01
* Cuvo, A. J. Translating Conceptual Variables to Measurable Variables
* Cuvo, A. J. Documenting Client Progress
Huck Chap. 4
* Anastasi, A. & Urbina, S. (1997). Psychological testing (7th ed.).Upper Saddle
River, NJ: Prentice Hall Chaps. 4-5. (You should understand each type of
reliability and
validity. What is its purpose? How does one establish the specific type of
reliability and
validity procedurally? Which ones would you use in a particular situation?)
QUIZ 3
***February 1, 2001 (Pseudo- or Pre-Experimental Designs)
Readings:
* HCB (1st. Ed.), Chap. 11 (focus on experimental design and not statistical
analysis)
Christensen, pp.232-238.
* Holden, P. & Neff J. A. (2000). Intensive outpatient treatment of persons with
mental retardation and psychiatric disorder: A preliminary study. Mental
Retardation,
38, 27-32. (Focus on design and not data analysis. What pre-experimental
design was
used? What research questions can it and can it not answer?)
QUIZ 4
***February 6, 2001 (Internal-Validity)
Readings:
Christensen, Chap.7
Re-read the HCB Chap. 11 from last class and focus on internal validity of
designs.
* Cuvo, A. J. Threats to Internal Validity in Experimental Research
* Cuvo, A. J. A Note on Testing as a Threat to Internal Validity and Pretest and
Posttest Sensitization as Threats to External Validity. (Read first paragraph)
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* Kruger, J., Savitsky, K., & Gilovich, T. (1999). Superstition and the regression
effect. Skeptical Inquirer, 23(2), 24-29.
QUIZ 5
***February 8, 2001 (Quasi-Experimental Designs)
Readings:
* HCB (1st. Ed.), Chap. 14 (up to p.323, focus on experimental design and not
statistical analysis)
Christensen, Chap. 10
The following articles involve quasi-experimental designs. Understand which
specific design was employed, what research question(s) it can and cannot
answer,
and how well this design controls for threats to internal validity.
* Slate, J. R., & Jones, C. H. (1989). Can teaching of the WISC-R be improved?
Quasi-experimental exploration. Professional Psychology: Research and
Practice, 20,
408-410.
* Schnelle, J.F. & Lee, J.F. (1974). A Quasi-experimental retrospective
evaluation of a prison policy change. JABA, 7, 483-496.
* Wilderman, R. (1981). Psychotherapy in a community mental health facility.
Evaluation and the Health Professions, 4,189-205.
QUIZ 6
***February 13, 2001
TEST 1
***February 15, 2001 (True Experimental Designs & External Validity)
Readings:
Note: True experimental designs control for most threats to internal validity by
random assignment of subjects to conditions, and do not require an individual
analysis
of the plausibility of each threat as was the case for pre-and quasi- experimental
designs.
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* HCB (1st ed.), Chap. 12 (Focus on design issues and not data analysis. The
use of gain scores and the independent t test are not a recommended approach
to
statistical analysis for the pretest-posttest control group design as suggested in
this
chapter. When you use a gain score, you lose the reliability of the underlying
measurement that was the basis for calculating the gain score. The pretestposttest
control group design is also called a Two Factor Mixed Design with One
Repeated
Measure. You will learn about an ANOVA for this design in a future class).
* Cuvo, A. J. A Note on Testing as a Threat to Internal Validity and Pretest and
Posttest Sensitization as Threats to External Validity. (Read all. See previous
class)
Christensen Chaps. 8 (Except sections on counterbalancing) & 14
* Designing research studies in psychology
http://gateway1.gmcc.ab.ca/~digdonn/psych104/var.htm (Download from
Internet)
* Class Exercise-matching and randomization-Take these to class
QUIZ 7
***February 20-27, 2001 (Basic Statistical Issues)
Readings:
2/20/01
Christensen, Chap.12
Huck, Chap. 2
* Normal Curve
QUIZ 8
2/22/01
Huck, Chaps. 5-6
* Cuvo, A. J. & Hewes, R. L. Population & Sampling
QUIZ 9
2/27/01
Huck, Chaps. 7-9
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QUIZ 10
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***March 1, 2001 (T-Tests)
Readings:
You need to understand the logic of the t-test as represented in the formula.
What does the numerator mean? What does the denominator mean? What does
the t
test do and how does it do it? What does the calculated value of t really mean?
Re-read comments above about not using t test for pretest-posttest control
group design under introduction to True Experimental Design.
Huck, Chap.11 (Skip sections on “Inferences Concerning a Single Mean”,p.285290.
Christensen, pp. 326-335.
* Independent t Test Example (This analysis was done on the Excel
software and serves as a model for Project 1. This provides you an applied
research
example where the independent t test was used. )
* Dependent t Test Example (This analysis was done on the Excel
software and serves as a model for Project 1. This provides you an applied
research
example where the dependent t test was used.)
* Cuvo, A. J. & Hewes, R. L. Using t Tables (Includes “Critical Value of
‘Student’s’ t statistic”)
* Holden, P. & Neff, J. A. (2000). Intensive outpatient treatment of persons with
mental retardation and psychiatric disorder: A preliminary study. Mental
Retardation,
38, 27-32. (See pseudo-experimental design class. Focus on data analysis and
interpretation)
* Cuvo, A. J. Effect of Within Groups Variability on the t Test
QUIZ 11
***March 5, 2001
Applied Exercise 1 - Conduct a literature review, derive a research question, and
design
an experiment whose data would be analyzed by either an independent or
dependent t
test. Generate hypothetical data for this exercise. Use the Experimental
Research
Design Form to do this and attach a table of the raw data for each experimental
condition, and a computer printout of results. Include in your data analysis the M
and
S.D. for each experimental condition. Do statistical analysis using any computer
and
software of your choice. State at the top of your report the name of the computer
and
software. The t test examples on the reading list provide models for this project.
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***March 6-8, 2001 (One Way ANOVA; Post hocs.)
Readings:
3/6/01
Huck, Chap. 12
* Cuvo, A. J. The logic of ANOVA (You need to know the logic of the ANOVA as
represented in the formula and discussed in this paper. How are the components
of
ANOVA calculated?)
* Cuvo, A. J. & Hewes, R. L. Using F tables (Includes “Percent Points in the F
Distribution”).
* Read the relevant section of Cuvo, A. J. Relationship Between Experimental
Design and ANOVA (See Mixed Factorial Design Class below)
QUIZ 12
3/8/01
Huck, Chap. 13
* The Tukey test and table (Note: A post-hoc test, such as the Tukey test, will be
needed for any significant F that is based on 3 or more means. The n per group
is
based on the number of subjects that went into the calculation of the mean per
group.)
* Kregel, J., Wehman, P., & Banks, P. D. (1989). The effects of consumer
characteristics and type of employment model on individual outcomes in
supported
employment. JABA, 22, 407-415. (Focus on ANOVA and post-hoc analyses and
not
chi-square analyses)
* ANOVA For One factor CRD (For this and subsequent computer analyses,
focus on the example of applied research and interpretation of results rather than
the
mechanics of the computer data analysis.)
QUIZ 13
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***March 20, 2001
TEST 2
***March 22-27, 2001 (Between Subjects & Randomized Blocks Designs)
Readings:
Huck, Chap. 14
* HCB (1st ed.) pp. 281-284.
Christensen, pp. 246-252, 346-357.
Note: If an ANOVA has both significant main effects and interactions, you will
have to compute more than one Tukey test because the q value and the n per
group,
which is in the denominator under the square root, will change. The n per group
is
based on the number of subjects that went into the calculation of each mean for
rows,
columns, or cells. The Tukey critical difference will not be the same for main
effects and
interactions when they differ with respect to number of means and n per group.
Assume
a 2 Factor Completely Randomized Design with 2 levels on Factor A and 3 levels
on
Factor B. Further assume that there are 10 subjects per cell or a total of 60
subjects
(2X3X10=60). If the F for Factor A is significant, no post-hoc test would be
needed
because there are only 2 levels and 2 means involved. If the F for Factor B is
significant, you will have to calculate a Tukey based on a q involving the 3 means
for
the three levels of the independent variable, and an n of 20 subjects per row
group. In
this case, the group is one entire row or column that contributes to the mean. For
the
interaction, there are 6 means for the 6 cells (2x3) in the design and an n of 10
per
group. The MS within group or error will be the same for all Tukey tests based on
the
same ANOVA because there is only one MS error in the ANOVA.
* Read about the relevant designs on Cuvo, A. J., Relationship Between
Experimental Design and ANOVA (See Mixed Factorial Design Class)
* Kennel, R. G. & Agresti, A. A.. (1995). Effects of gender and age on
psychologists’ reporting of child sexual abuse. Professional Psychology:
Research
and Practice, 26, 612-615. (Explain the experimental design. Focus on ANOVA
and
Post-hoc analyses and not chi-square analyses)
* Bordieri, J. E., Comninel, M. E., & Drehmer, D. E. (1989). Client attributions for
disability: Perceived accuracy, adjustment, and coping. Rehabilitation
Psychology, 34,
271-278. (Explain the experimental design.)
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* ANOVA for a 2 factor CRD (This is a general model for your next project. This
example has two IVs with only 2 levels on each IV. Your project, in contrast, has
2 IVs
with 3 levels on each IV. It might be a good idea to run this analysis with the data
in
your handout as a practice for your next project. You will have to generalize from
this
example to entering one more level on the 2 IVs).
* ANOVA for a Randomized Block Design (Treatment by Levels)
* Cuvo, A. J. Possible Outcomes for a Two factor Experiment (Look at this
handout to see all possible outcomes from a 2 factor experiment. You should be
able to
explain each outcome and draw the appropriate figure.)
Huck, Chap.15
* ANOVA for a 3 factor CRD
QUIZ 14 3/27 only, based on readings for both dates. No quiz on 3/22.
April 2, 2001
Applied Exercise 2 - Conduct a literature review, derive research questions, and
design
an experiment with two between subjects independent variables with two levels
on each
variable. Generate hypothetical data for this exercise, and do so in a manner that
results in at least one significant main effect and an interaction. This means that
you
have to understand the concept of how a main effect and interaction are created.
Use
the Experimental Research Design Form to do this, and attach a table of the raw
data
for each experimental condition, and a computer printout of your results. Do
statistical
analysis using a computer and software of your choice. Name them at the top of
your
report. Your report should include the M and S.D. for each condition, the
complete
ANOVA table, a graph of the interaction, post-hoc tests as needed (do by hand if
computer program does not do this and show step-by-step computations). For
your
report, note that an interpretation of results is a description of which conditions
are and
are not significantly different from each other, and not just a statement of the
statistics.
Remember that the interaction qualifies the interpretation of the main effect. The
ANOVA for a 2 Factor CRD example on the reading list provides a model for this
project. You will have to generalize to three levels on the independent variables.
EXCEL
will not do this analysis. You could use Statview available in the College of
Education
Computer Lab.
***March 29, 2001 (Repeated Measures Factorial Designs)
Readings:
Huck, Chap. 16
Christensen, pp. 252-255.
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Cuvo, A. J. A Note on Test Scores as a Dependent Variable and Test Trials as
an Independent Variable.
* Read the relevant section of Cuvo, A. J. Relationship Between Experimental
Design and ANOVA (See Mixed Factorial Design Class below)
Christensen, Chap. 8 (sections on counterbalancing only. See True Experimental
Design class)
* Cuvo, A. J. Crossover or Changeover Design
* Fujiki, M. & Brinton, B. (1993). Comprehension monitoring skills of adults with
mental retardation. Research in Developmental Disabilities, 14, 409-421.
Re-read Slate & Jones (see quasi-experimental design class) and focus on
data analysis
QUIZ 15
***April 3, 2001 (Mixed Factorial Designs)
Readings:
Huck Chap. 17
Christensen, pp. 255-259.
* Finlayson, L. M., & Koocher, G. P. (1991). Professional judgment and Child
abuse reporting in sexual abuse cases. Professional Psychology: Research and
Practice, 22, 464-472. (Explain the experimental design and data analysis.)
* Keefe, F. J., Surwit, R. S., & Pilon, R. N. (1980). Biofeedback, autogenic
training, and progressive relaxation in the treatment of Raynaud's disease: A
comparative study. JABA, 13, 3-11. (Explain the experimental design and data
analysis.)
* ANOVA for a 2 Factor Mixed Design
* Cuvo, A. J. Factors That Affect F
* Cuvo, A. J. Relationship Between Experimental Design and ANOVA
QUIZ 16
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***April 5, 2001 (ANCOVA)
Note: ANCOVA is a statistical test and not an experimental design. It can be
used instead of an ANOVA in any of the experimental designs presented above.
ANCOVA provides statistical control rather than control using experimental
design
tactics. You should understand the situations for which ANCOVA is the more
appropriate analysis than ANOVA, and the logic of how it works.
Readings:
Huck, Chap. 18
* Kottke, J. L., Mellor, S., Schmidt, A. C. (1987).Effects of information on
attitudes toward and interpersonal acceptance of persons who are deaf.
Rehabilitation
Psychology, 32, 239-243.
* ANCOVA for Pretest Posttest Control Group Design
QUIZ 17
***April 10, 2001 (MANOVA & MANCOVA)
Note: MANOVA and MANCOVA are used to analyze data from multivariate
experiments (i.e., those with more than one dependent variable). You should
understand the rationale for using MANOVA and MANCOVA, instead of ANOVA,
how
these multivariate tests generally operate, and how to interpret results from these
analyses.
Readings:
* HCB (1st ed.) Chap. 9 Multivariate Analogs to the T Test , ANOVA, & ANCOVA
Reexamine Huck pp. 203-208, the data analysis in the Wilderman article,
discussion of Bonferroni inequality test in Finlayson & Koocher (p. 468).
* Church, P., Forehand, R., Brown, C., & Holmes, T. (1990). Prevention of
drug abuse: Examination of the effectiveness of a program with elementary
school Children. Behavior Therapy, 21, 339-347.
* Cuvo, A. J. Data Analysis Discriminations-Section A
QUIZ 18
***April 12, 2001
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TEST 3
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***April 17-29, 2001 (Nonparametric Statistics)
Readings:
4/17/01
Note: Nonparametric statistics is a class of statistics used to analyze data that do
not meet the assumptions of parametric statistics. Previous chapters have stated
assumptions for parametric tests, and you should understand these assumptions.
Furthermore, you should understand conditions that violate these assumptions,
and use
the Nonparametric Statistic Tests chart to identify an appropriate statistic for
analyzing
the data. A primary learning objective for you is to use the “Nonparametric
Statistic
Tests” chart to identify an appropriate nonparametric statistic for a research
situation.
Use the past test and quiz questions to practice.
*Siegel, S. & Castellan, N. J., Jr. (1988). Nonparametric Statistics (2nd. ed.) (pp.
19-36, Nonparametric Statistics Tests table). New York: McGraw-Hill. The
objective for
the table at the end of the chapter is for you to learn to make the necessary
discriminations about a research context (i.e., level of measurement, number of
cases,
whether they are related or independent) to identify the nonparametric tests that
would
be appropriate for the situation. At that point, you would have to read in greater
detail
about how to perform the tests. This table would be made available on the last
test if
there are related questions.
Huck, Chap. 20
* Amick-McMullan, A., Kilpatrick, D. G., & Resnick, H. S. (1991). Homicide as a
risk factor for PTSD among surviving family members. Behavior-Modification, 15,
545559.
Re-read Kennel & Agresti (1995) and Kregel et al. (1989) above and focus on
how statistical analyses change to fit the research questions asked and data
characteristics.
* Complex Chi Square and the Contingency Coefficient
* Chi Square as a Test of Independence
QUIZ 19
4/19/01
Huck, Chap. 21
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* Callahan, W. P. (1983) The effectiveness of instructional programming on the
reduction of dental disease in mentally retarded individuals. Mental Retardation,
21,
260-262.
* Mann Whitney U Test
* Wilcoxon Matched Pair Signed Rank Test
* Friedman Two Way ANOVA by Ranks
* Kruskall-Wallis One Way ANOVA by Ranks
* Review Data Analysis Discriminations-Section A
QUIZ 20
***April 24-26, 2001 (Bivariate Correlation)
Note: The data analysis techniques at this point in the course take a different
turn. The correlational statistics are used to answer research questions
pertaining to the
relationship or degree of association between variables, and how well several
variables
taken together can predict one or more criterion variables. This type of research
question is in contrast to previous research questions pertaining to the
significance of
difference between population parameters. Correlational analyses can make use
of
measured variables (i.e., Ss are simply evaluated and scored on various
dependent
measures) and not manipulated variables in the context of experimental design
as you
saw previously. Although there are ostensible differences between tests of
significance
of difference and correlational procedures, they are fundamentally the same. For
all the
bivariate and multivariate analyses, the goal should be for you to have an
understanding of what these tests show in a practical sense. You need not
remember
formulas here.
Readings:
Huck, Chaps. 3 & 10
Correlational vs. experimental studies
http://gateway1.gmcc.ab.ca/~digdonn/psych104/cor.htm (Download from
Internet)
* Appropriate Correlational Techniques for Different forms of Variables (The key
to understanding correlational techniques is to determine how many variables
there are,
their level of measurement, and whether they are predictor or criterion variables.
A
primary learning objective for you is to use the page titled Appropriate
Correlational
Techniques for Different forms of Variables to identify an appropriate
correlational
statistic for a research situation. Use the past test and quiz questions to practice.
If
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there are questions relevant to this on the last exam, this page will be made
available to
you.)
* Range of values of r (You should understand the shape and slopes for the
various correlations)
* Critical Values of Pearson r (Note: n’ refers to pairs of scores being correlated.
This table is used similar to that for the t test. You enter it with the appropriate df
and
alpha level and find the critical value of r.)
* Hodapp, R. M., Evans, D. W., & Ward, B. A. (1989).Communicative interaction
between teachers and children with severe handicaps. Mental Retardation, 27,
388395.
* Pearson Product-Moment Correlation
* Spearman Rank-Order Correlation
* Point Biserial Correlation Coefficient
Read the following news announcement and infer how the study was conducted.
What
can be said about a cause and effect relationship between drinking coffee and
getting
colorectal cancer?
Coffee may cut colon cancer risk
(Reuters) - Coffee drinking has been linked to a lower risk of
colorectal cancer in a majority of recent studies, according to a
review published in the current issue of the American Journal of
Epidemiology. Dr. Edward Giovannucci of the Harvard School of
Public Health, Boston, Massachusetts, writes that "a lower risk
of colorectal cancer is associated with higher levels of coffee
consumption."
QUIZ 21 4/26 only, based on readings for both dates. No quiz on 4/24
***April 30, 2001
Applied Exercise 3 - Write a research question that asks about the degree of
relationship between two plausible variables relevant to human services. Name
the
variables that you are measuring and state their level of measurement. Generate
20
hypothetical scores on each variable and do the appropriate statistical analysis
by
computer. In addition to the information stated above, include in your report the
name
of the computer software, raw data, null and alternative hypotheses, name of
statistical
test, appropriately labeled scatterplot of data which could be done by hand or
computer,
statistical results including critical value of the statistic, calculated value of the
statistic,
percentage of variance explained, and interpretation of results including decision
REHB 509B Syllabus
21
regarding Ho. The interpretation should describe the specific relationship
between the
variables (e.g., as people get older, they tend to get heavier). If any of the
information
requested is on printouts, please put it in your report. Note that this project is
done on
your own paper and not the form that you used for the previous two projects. Be
sure
your report includes all the items cited above. The Pearson Product Moment
Correlation
example on the reading list provides a model for this project.
*** May 1-3, 2001 (Multiple Regression Analysis)
Readings:
* HCB (1st ed.) Chap. 8. Multiple Correlation & Discriminant Function Analysis
(Read up to p.160 for 5/1/01.)
Huck Chap. 19 (read pp. 565-589 for 5/1/01 and rest of chapter for 5/3/01)
* Multiple Regression Examples (5/1/01)
* Listing a House with a Big Real Estate Agency (Relate this article to the
elements of multiple regression-5/1/01)
* Spence, S. H. (1981).Validation of social skills of adolescent males in an
interview conversation with a previously unknown adult. JABA, 14, 159-168.
(Understand how multiple regression was conducted in a series of steps to
answer a
question about social validation 5/1/01).
* Parker, R. M. & Szymanski, E. M. (1999). Recommendations of the APA task
force on statistical inference. Rehabilitation Counseling Bulletin, 43, 3-4. (5/3/01)
* Read Data Analysis Discriminations-Section B (5/3/01)
QUIZ 22 5/3 only, based on readings for both dates. No quiz 5/1
***May 9, 2001
TEST 4 1:00-2:15PM Room TBA