4. Part 3. This question asks you to use the 2014 BRFSS data (SAS Transport formats). Codebook is presented in codebook2014_brfss.pdf. Please complete the following tasks. Please submit your SAS codes, SAS log file, SAS lst file for Q2. In your SAS lst file, please highlight the percentages or means you used to summarize and interpret your results.
1. Go online to download the 2014 BRFSS dataset. The zipped file is about 64 mb. So, make sure that you have adequate space to save the dataset. (2 pts)
https://www.cdc.gov/brfss/annual_data/annual_2014.html
2. Write SAS codes to create a permanent SAS dataset. (1 pt)
3. Using BRFSS codebook, identify the variable for “frequency of days now smoking”. Please recode this variable into two categories, 1= (every day or some days), 0=(not at all). All other categories can be coded as missing. (2 pts)
4. Identify one variable, which may be related to current smoking status. Please conduct bivariate analyses of this variable with participant’s current smoking status variable (dichotomous) that you created in iii). Remember that you need to consider the complex survey design in BRFSS. (3 pts)
5. Present and interpret your results. (3 pts)
Part 4. Complete the following tasks using a linked birth and death certificate dataset (qs4.sas7bdat):
We created a linked dataset of birth certificates and death certificates in South Carolina, restricting to all infant deaths under age one (n=313) and a random sample of live births (n=687) who survived through the first year (about 1:2 ratio). Below is a description of limited variables included in the dataset.
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