Description
tep 1: Merge the data files that you will be using for your project together by SEQN so that all your data is in one file (name: merged_file). Remember to sort your data files by SEQN before merging. Use (in = x) options to keep only data for individuals that appear in all data files. Step 2: Report the number of observations in each of your data files. Report the number of observations in your merged_file. Did you lose a large proportion of your sample? If so, which data file contributed most to the loss in sample size?Step 3: In your merged_file, use a keep statement to identify all the variables that you will use in your analyses. Remove all other columns. Report the number of variables remaining in your merged file. Step 4: Use formats to add labels to response options for all categorical variables in your analytic file (e.g. 1 = yes, 0 = no)Step 5: Use label statements to update labels for all variables in your data file if necessaryStep 6: Check your merged data file by running a PROC CONTENTS to examine the metadata and PROC PRINT to examine individual data values for first 20 people in your data file. Include a copy of the output here.Step 7: Download and submit a copy of the log after running the steps above. Please make sure all errors and warnings were resolved prior to submitting. SAS code should be commented with descriptions of each step.
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Assignment 3
Step 1: Merge the data files that you will be using for your project together
by SEQN so that all your data is in one file (name: merged_file).
Remember to sort your data files by SEQN before merging. Use (in = x)
options to keep only data for individuals that appear in all data files.
Step 2: Report the number of observations in each of your data files.
Report the number of observations in your merged_file. Did you lose a
large proportion of your sample? If so, which data file contributed most to
the loss in sample size?
Step 3: In your merged_file, use a keep statement to identify all the
variables that you will use in your analyses. Remove all other columns.
Report the number of variables remaining in your merged file.
Step 4: Use formats to add labels to response options for all categorical
variables in your analytic file (e.g. 1 = yes, 0 = no)
Step 5: Use label statements to update labels for all variables in your data
file if necessary
Step 6: Check your merged data file by running a PROC CONTENTS to
examine the metadata and PROC PRINT to examine individual data values
for first 20 people in your data file. Include a copy of the output here.
Step 7: Download and submit a copy of the log after running the steps
above. Please make sure all errors and warnings were resolved prior to
submitting. SAS code should be commented with descriptions of each step.
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