Assignment Part I
You will complete this part of the assignment using SPSS Statistics.
You have been provided a data set, HELP, in Excel format (posted on BB under HW3) that includes scores on factors pertaining to the mental health of a person. The descriptions for the variables in the dataset are as following:
|
Variable |
Label |
|
Age |
Age at baseline (in years) |
|
Female |
Gender of the respondent, 0= Male, 1=Female |
|
PSS_FR |
Perceived Social Support from Friends |
|
Homeless |
One or more nights on the street or shelter in past 6 months, 0= Not Homeless, 1= Homeless |
|
PCS |
Physical Health Composite Score-Baseline for a person |
|
MCS |
Mental Health Composite Score – Baseline for a person |
|
CESD |
Total Score, Baseline for a person. |
For Part I of the homework, you will be looking at mental health for the subjects for whom details are provided in the dataset, HELP. First, you will be running a model to look at the continuous measure “MCS” which is the mental component score of the SF-36 quality of life instrument/questionnaire. The MCS values range from 0 to 100 where the population norm for “normal mental health quality of life” is considered to be a 50. If you score higher than 50 on the MCS you have mental health better than the population norm and vice versa - if your MCS scores are less than 50 then your mental health is considered to be worse than the population norm.
Learn more about MCS at MCS
Here is a list of tasks that you need to perform using SPSS Statistics for HELP dataset.
1. Run a simple linear regression for MCS variable (using it as a dependent variable) using the CESD variable as predictor variable (which is a more specific measure for depression). Write the equation of the final fitted model (i.e. what is the intercept and the slope)? Write a sentence describing the model results (interpret the intercept and slope). Copy/paste Coefficient Table from SPSS Statistics output below.
[INSERT RELEVANT OUTPUT HERE]
2. How much variability in MCS variable does the CESD variable explain? (What is the value of R2?) Write a sentence describing how well the CESD variable does in predicting the variable MCS?
3. Run a second linear regression model for the MCS variable putting in all of the other variables in the data subset as predictor variables:
Copy/Paste the model results with the coefficients and tests and model fit statistics below.
[INSERT RELEVANT OUTPUT HERE]
4. Which variables are significant in the model? Write a sentence or two describing the impact of these variables for predicting mental component scores. Run the VIFs to check for multi-collinearity issues. Identify the variables with multi-collinearity issues. Copy/Paste the output with VIF values for each variable.
[INSERT RELEVANT OUTPUT HERE]
5. Remove the variables which are not significant in the model in part 4 above and those which VIF more than 4 and run it again. Copy/Paste the model results with the coefficients and tests and model fit statistics below. Which variables are significant now?
[INSERT RELEVANT OUTPUT HERE]
6. Which model (from part 1 and 2 or the one from part 3 and 4 or part 5) is better to explain the dependent variable, MCS? Write your answer and explain why you think this model is better than others?
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