Data Screening and Analysis of GAF Scores and Consumer Satisfaction Across Health Agencies � Grand Canyon University
Comparative analysis of GAF scores and consumer satisfaction in mental health agencies.
Amelia Davis
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College of Doctoral Studies
© 2013. Grand Canyon University. All Rights Reserved.
Data Screening and Analysis of GAF Scores and Consumer Satisfaction Across Public and
Private Mental Health Agencies – Grand Canyon University
Assignment
GAF, Consumer Satisfaction, and Type of Clinical Agency (Public or Private)
A researcher wants to know if mental health clients of private versus public service agencies
differ on Global Assessment of Functioning (GAF) scores and on Satisfaction with Services
(Satisfaction). She has collected data for 34 clients from a private agency and for 47 clients of a
public agency.
Directions:
Use the SPSS data file for Module 3 (located in Topic Materials) to answer the following
questions:
1. What is the independent variable in this study? What are the dependent variables?
Solution: The independent variable in the study is the GAF (Global Assessment of Functioning)
and satisfaction level with the services named as Satisfaction. There is also a dummy variable
which is of value 2 for public and 1 for private.
2. The first step for the researcher will be to clean and screen the data. Please do this for the
researcher and report your findings. Be sure to check it for possible coding errors, as well as
complete the screening of the data to see if the data meet assumptions for parametric tests. Did
you find any errors that the researcher made when setting up the SPSS data file (check the
variable view)? If so, what did you find? How did you correct it?
Solution: The measure of a dummy variable cannot be as scale, so the category must be changed
to ordinal. Data doesn’t meet the requirements of parametric test as the parameters have too
many missing values. For correcting definition of the variables the data can be selected from the
panel and from the drop box menu required value can be selected.
© 2013. Grand Canyon University. All Rights Reserved.
Data Screening and Analysis of GAF Scores and Consumer Satisfaction Across Public and
Private Mental Health Agencies – Grand Canyon University
Assignment
GAF, Consumer Satisfaction, and Type of Clinical Agency (Public or Private)
A researcher wants to know if mental health clients of private versus public service agencies
differ on Global Assessment of Functioning (GAF) scores and on Satisfaction with Services
(Satisfaction). She has collected data for 34 clients from a private agency and for 47 clients of a
public agency.
Directions:
Use the SPSS data file for Module 3 (located in Topic Materials) to answer the following
questions:
1. What is the independent variable in this study? What are the dependent variables?
Solution: The independent variable in the study is the GAF (Global Assessment of Functioning)
and satisfaction level with the services named as Satisfaction. There is also a dummy variable
which is of value 2 for public and 1 for private.
2. The first step for the researcher will be to clean and screen the data. Please do this for the
researcher and report your findings. Be sure to check it for possible coding errors, as well as
complete the screening of the data to see if the data meet assumptions for parametric tests. Did
you find any errors that the researcher made when setting up the SPSS data file (check the
variable view)? If so, what did you find? How did you correct it?
Solution: The measure of a dummy variable cannot be as scale, so the category must be changed
to ordinal. Data doesn’t meet the requirements of parametric test as the parameters have too
many missing values. For correcting definition of the variables the data can be selected from the
panel and from the drop box menu required value can be selected.
© 2012. Grand Canyon University. All Rights Reserved.
3. Were there missing values on any of the variables? If so, what might you do for those for the
independent variable? What about those for each of the dependent variables? Explain your
reasoning.
Solution: Yes, there are missing values. Yes there are missing values for independent and
dependent values as well. There are 9 values missing in 82 entries of independent variable GAF
which is 10.9%. There are 11 missing values for independent variable satisfaction out of 82
which is 13.4%. There is one missing value for dummy variable also. The entry which has
missing values for all the variables can be deleted. Now, we have independent variable GAF
with 8 missing values and independent variable Satisfaction with 10 missing value.
4. Did you find any outliers on the dependent variables that were due to errors of coding? If so,
what and why? How would you correct an error of coding?
Solution: Yes, independent variable GAF has a value of 201 which can be regarded as an outlier.
The entries with outlier values for coding errors must be deleted to get the accurate results.
5. How might you deal with outliers that are not due to coding errors? Explain your reasoning.
Solution: Outlier without the coding error generally have a significant role in forming the results
and thus must be left unchanged, they might vary the descriptive statistics but gives additional
information regarding our model.
3. Were there missing values on any of the variables? If so, what might you do for those for the
independent variable? What about those for each of the dependent variables? Explain your
reasoning.
Solution: Yes, there are missing values. Yes there are missing values for independent and
dependent values as well. There are 9 values missing in 82 entries of independent variable GAF
which is 10.9%. There are 11 missing values for independent variable satisfaction out of 82
which is 13.4%. There is one missing value for dummy variable also. The entry which has
missing values for all the variables can be deleted. Now, we have independent variable GAF
with 8 missing values and independent variable Satisfaction with 10 missing value.
4. Did you find any outliers on the dependent variables that were due to errors of coding? If so,
what and why? How would you correct an error of coding?
Solution: Yes, independent variable GAF has a value of 201 which can be regarded as an outlier.
The entries with outlier values for coding errors must be deleted to get the accurate results.
5. How might you deal with outliers that are not due to coding errors? Explain your reasoning.
Solution: Outlier without the coding error generally have a significant role in forming the results
and thus must be left unchanged, they might vary the descriptive statistics but gives additional
information regarding our model.
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Subject
Psychology