according to the output, do you think the variable ‘BMICAT’ is correctly coded explain why or why not

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Question 1 is based on the NHANES 6-year data. You can find the description of variables in its codebook (attached with final project in Carmen).

1. (20 points)

(a)     (i)  Read/load the dataset ‘nhanes_6yr.sas7bdat into SAS.

(ii)   Update the loaded data in SAS by creating the variables BMICAT and HYPTS using the following conditions.

Hint: consider the length of the characters for the new variables when writing your code

Note: Here, do not exclude respondents with missing values for any of the

variables.

If the body mass index (BMI) is missing, then BMICAT is equal to “Missing”. For non-missing values, BMICAT is “Underweight” if body mass index (BMI) is less than 18.5, BMICAT is “Healthy” if BMI is 18.5 but less than 25, BMICAT is “Overweight” if BMI is 25 but less than 30, and BMICAT is “Obese” if BMI is 30 and above.

If both systolic blood pressure and diastolic blood pressure are missing, then HYPTS is equal to “Missing”. For non-missing values, HYPTS is equal to “Prehypertension/Stage 1 or 2 HTN” if systolic blood pressure is greater than or equal to 120 or if diastolic blood pressure is greater than or equal to 80. And HYPTS is equal to “No hypertension” if systolic blood pressure is less than 120 and if diastolic blood pressure is less than 80. 

            Also, create labels for the variables BMICAT and HYPTS as follows:

BMICAT          ~          BMI Categories

HYPTS             ~          Hypertension Status

(iii)       From your updated data (in part-a-ii), use PROC MEANS (with appropriate title) to check whether the variable ‘BMICAT’ is correctly coded. 

Copy and paste your output from your PROC MEANS (with an appropriate title) here.

According to the output, do you think the variable ‘BMICAT’ is correctly coded? Explain why or why not.

 (iv)   Using your updated data (part-a-ii), print out the third 20 observations for only the variables SEQN, BMICAT, and HYPTS. To obtain full credit, ensure that your output contains the labels for each variable (and not the variable names). 

Attachments:

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