To study factors related to the diagnosis of depression in primary care, 400 patients were randomly selected and the following variables were recorded:

DAV: Diagnosis of depression in any visit during one year of care.
0 = Not diagnosed
1 = Diagnosed

PCS: Physical component of SF-36 measuring health status of the patient.
MCS: Mental component of SF-36 measuring health status of the patient
BECK: The Beck depression score.
PGEND: Patient gender

0 = Female
1 = Male

AGE: Patient’s age in years.

EDUCAT: Number of years of formal schooling.

The response variable is DAV (0 not diagnosed, 1 diagnosed), and it is recorded in the first column of the data. The data are stored in the file final.dat and is available from the course website. Perform a multiple logistic regression analysis of this data using SAS or any other statistical packages. This includes estimation, hypothesis testing, model selection, odds ratios, residual analysis and diagnostics. Explain your findings in a 3 to 4- page report. Your report may include the following sections:

• Introduction: Statement of the problem.
• Material and Methods: Description of the data and methods that you used for the analysis.
• Results: Explain the results of your analysis in detail. You may cut and paste some of your computer outputs and refer to them in the explanation of your results.
• Conclusion and Discussion: Highlight the main findings and discuss.

Please cut and paste the computer outputs to your report and do not include any direct computer output as an attachment

Please note that you have also the option of using a similar dataset in your own field of interest.

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I. Introduction

In this paper, we will examine the factors related to the diagnosis of depression in primary using a data for 400 patients.

II. Materials and methods

The response variable is a binary variable i.e. either diagnosed (1) or not diagnosed (0). On other other hand, the predictive variables are
• pcs – physical component of SF-36 measuring health care of the patient (a continuous variable)
• mcs – mental component of SF-36 measuring health status of the patient (a continuous variable)
• beck – the beck depression score (a continuous variable)
• pgend – patient’s gender (a categorical variable)
• age – patient’s age in years (a continuous variable)
• educat – total years of formal schooling
Since the response variable is categorical, we will use multiple logistic regression model and let’s check which variables we should include in the model.
III. Results and Conclusions

In all our analysis, we use R statistical software, using the function glm()....

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