Homework 2 2014.doc - 1 Download the dataset hw2.sas7bdat(available from the course website under the homework page It is restricted to subjects with

Homework 2 2014.doc - 1 Download the dataset...

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1. Download the dataset hw2.sas7bdat (available from the course website under the homework page). It is restricted to subjects with complete data on the variables listed above. Create the following variables: - BMI (continuous): calculated by [weight (kg)/ (height(m)) 2 ] - Gender: recode sex as 0=female, 1=male and use this variable in this homework - Alcohol consumption status (binary variable such as 0 corresponds to zero drink/week and 1 corresponds to more than zero drinks/week) Please provide SAS code as the answer to this question. /* Q1 */ data HW2; set "P:\Spring 2014\EPI204\hw2.sas7bdat" ; bmi = wt/((height/ 100 )*(height/ 100 )); sex = (sex*- 1) + 2 ; boozecat = (booze = 0 ); run ; 2. Fit a regression model for systolic blood pressure (sbp) including age, BMI, race (referencecategory=other), sex, smoking status, alcohol consumption status, and hdl (no productterms). What are the assumptions for linear regression? 1) Normality: ε i ~ N(0, σ 2 ) 2) Linearity: the relationship between age, BMI, HDL, and expected systolic blood pressure are linear. 3) Independence between observation errors: ε i ε j 4) Homoskedasticity of errors: constant variance of residuals Are there any other assumptions you are making in this model? Yes. If so, what are they? 1) There exists no interaction between any of the covariates or with BMI in predicting SBP. 2) The effects of race and alcohol consumption status on expected SBP are constant within levels of race and alcohol consumption status. 3) Covariates are additive with respect to expected SBP (i.e. no higher order terms). Provide a plot of the residuals. See next page for plot. 1
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Please provide the SAS code and the SAS model output as part of the answer to this question. See appendix. 3. Check the linearity assumption for BMI by adding a quadratic term for BMI to theprevious model. Is there any evidence that the quadratic term for BMI is appropriate in themodel?
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