By Everitt, Brian; Der, Geoff
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Extra info for Statistical analysis of medical data using SAS
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If the data contain missing values, it is important to allow for this when recoding. In numeric comparisons, missing values are treated as smaller than any number. For instance, if age >= 18 then adult=1; else adult=0; would assign the value 0 to adult if age was missing, whereas it may be more appropriate to assign a missing value. ; Care needs to be exercised when making comparisons involving character variables since these are case sensitive and sensitive to leading blanks. A group of statements may be executed conditionally by placing them between a do statement and an end statement.
Use the enhanced editor colour coding to double check. • Check any statement that does not begin with a keyword (blue or navy blue) or a variable name (black). • Large blocks of purple may indicate a missing quotation mark. • Large areas of green may indicate a missing */ from a comment. ‘Collapse’ the program to check its overall structure. Hold down the Ctrl and Alt keys and press the numeric keypad minus key. Only the data, proc statements, and global statements should be visible. To expand the program, press the numeric keypad plus key while holding down Ctrl and Alt.
For most of these the dsd option on the infile statement will suffice, as it assumes the delimiter is a comma. Some commadelimited files will have data values enclosed in quotes to avoid problems where data values include commas. The dsd option deals with this too by ignoring commas within quotes and removing the quotes from the data values. The missover option is also recommended for CSV files to prevent SAS going to a new line where the last value on a data line is missing. There is an example in Chapter 14.
