Analyze the Framingham Heart Study* dataset preloaded in SAS Studio. Produce a Logistic Regression Analysis for the Variables “Weight” and “Status”

ATTACHED FILE(S)

Instructions

SAS Assignment. Heart Data Analyses Worksheet #2
Instructions
AnalyzetheFraminghamHeart Study*dataset preloaded in SAS Studio.
Upload a FraminghamHeart Study*dataset provided by the textbook publisher in a CSV format.
*(see textbook Section 2.4)
Step 1 – Produce a Logistic Regression Analysis for the Variables “Weight” and “Status”* using the SASHELP.HEART dataset.
Week 3 Resources: Chapter 9 & Fit a Logistic Regression Model with SAS (i.e., video, PPT, code)
* Model status (event=’dead’) = weight;
Step 2 – Produce a Logistic Regression Analysis for the Variables “Weight” and “Status”* using the SASHELP.HEART dataset. Analysis Should be Restricted to One Sex (Male or Female).
Week 3 Resources: Chapter 9 & Fit a Logistic Regression Model with SAS (i.e., video, PPT, code)
* Model status (event=’dead’) = weight;
Step 3 – Upload the
HeartDataSet.csv
into SAS Studio. Create WORK.HEARTDATASET and Run a Proc Print.
Week 3 Resources: Reading and Generating CSV Files Using SAS Studio (i.e., video, PPT, code).
Step 4 – Complete & Submit “Heart Analyses Worksheet #2
Resources
·
Heart Analyses Worksheet
– Word Document(37.2 KB)
Note: Students can work in pairs to complete the assignment; however, each student must submit a completed worksheet.

Instructions

SAS Assignment. Heart Data Analyses Worksheet #2
Instructions
AnalyzetheFraminghamHeart Study*dataset preloaded in SAS Studio.
Upload a FraminghamHeart Study*dataset provided by the textbook publisher in a CSV format.
*(see textbook Section 2.4)
Step 1 – Produce a Logistic Regression Analysis for the Variables “Weight” and “Status”* using the SASHELP.HEART dataset.
Week 3 Resources: Chapter 9 & Fit a Logistic Regression Model with SAS (i.e., video, PPT, code)
* Model status (event=’dead’) = weight;
Step 2 – Produce a Logistic Regression Analysis for the Variables “Weight” and “Status”* using the SASHELP.HEART dataset. Analysis Should be Restricted to One Sex (Male or Female).
Week 3 Resources: Chapter 9 & Fit a Logistic Regression Model with SAS (i.e., video, PPT, code)
* Model status (event=’dead’) = weight;
Step 3 – Upload the
HeartDataSet.csv
into SAS Studio. Create WORK.HEARTDATASET and Run a Proc Print.
Week 3 Resources: Reading and Generating CSV Files Using SAS Studio (i.e., video, PPT, code).
Step 4 – Complete & Submit “Heart Analyses Worksheet #2
Resources
·
Heart Analyses Worksheet
– Word Document(37.2 KB)
Note: Students can work in pairs to complete the assignment; however, each student must submit a completed worksheet.
Logistic Regression Model
Survival on the RMS Titanic
Survival on the RMS Titanic (Cont.)
Survival on the RMS Titanic (Cont.)
Survived Variable
Survived Variable (Cont.)
Logistic Regression
LOGISTIC Procedure
DATA= Option
MODEL Statement
Predictors
EVENT=1
RUN Statement
Display Standard Input
Model Information
Relevant Information
Sample Size Information
Model Convergence
Model Fit Statistics
Model Fit Statistics (Cont.)
Model Fit Statistics (Cont.)
Testing Global Null Hypothesis
Testing Global Null Hypothesis (Cont.)
Testing Global Null Hypothesis (Cont.)
Analysis of Maximum Likelihood Estimates
Analysis of Maximum Likelihood Estimates (Cont.)
Odds Ratio Estimates
Odds Ratio Estimates (Cont.)
Odds Ration Estimates (Cont.)
Odds Ratio Estimates (Cont.)
Association of Predicted Probabilities and Observed Responses
Association of Predicted Probabilities and Observed Responses (Cont.)
Association of Predicted Probabilities and Observed Responses (Cont.)
Association of Predicted Probabilities and Observed Responses (Cont.)
Association of Predicted Probabilities and Observed Responses (Cont.)
PLOTS=EFFECT
Logistic Regression Effect Plot
Logistic Regression Effect Plot (Cont.)
Predicted Probabilities for Survived
Predicted Probabilities for Survived (Cont.)
Thank You