HRP223 - 2008

1. HRP223 - 2008 Topic 2 – Using EG

2. At this point you can: • Start up a project • Use SAS as a calculator • Set some configuration options • Remember to work in WORK, rather than SASUSER • Create a library • Import a dataset • into work or your custom library • Subset a dataset • You can use data steps, write or point/click to SQL

3. Working on a Project Set up a library to hold your permanent data. Import data into that library. Look at what you’ve got. Check for bad data. Subset the data to keep the data you want. Make a report.

4. Make the Library Tools menu > Assign Library… Review the code (if you want) Check the log

5. Write the Import Code Where is the dataset node in the flowchart? The log is good. It is a bug… they forgot to draw the dataset if you use proc import.

6. You really want to put the source file in the library. Tweak the code and link the import node to the library.

8. Files in a Library Once a file is in a library, you can access it just like any other file on your computer.

9. Structure • If you have a dataset on the left margin of a process flow, you will have a problem in your future. • Put every dataset into a library. • If your datasets move across machines you just need to change the one library reference path. • Add a note (File > New > Note) with information on the origin of every data file and connect it. • Include the time, date, and source of the file (email titles help also).

10. Add a Variable • To add a variable with EG: • Select the dataset • Choose Filter and Query…. from the Data menu • Name the query and new dataset • Select the current variables (drag and drop to select data) • Click Computed Columns • Click New, then click Build Expression • Fill in the expression and click OK • Select the new variable and give it a good name • Select the new variable (drag and drop to select data)

15. Calculate Stuff • Calculate the discounted price and then get some descriptive statistics on the new values. • Either reopen the previous filter and add in the formula there or just make a new data set by filtering the previously created data set.

16. Click on the data set to analyze or choose it from the list Proc Means Proc Univariate

17. Procs or Menu Items Use the task list (right side of the screen), organized by task name, to look up the procedures that go with a menu item or if you are told to use a procedure, you can find the corresponding menu item like this.

19. Not enough data for a useful histogram Be glad you did not need to memorize this stuff.

20. Looking at Categorical Data Drag Tour from the left pane and drop it into the Analysis variables group. In this source file we have a categorical “tour” variable. What are the its values? Use the Describe > One-Way Frequencies menu option to see the categories.

21. Proc Freak The procedure that does frequency counts is proc freq (pronounced freak). It is very important to learn because it does the core categorical analysis for basic epidemiological studies. The EG code is: This could be simplified PROCFREQDATA=day2.source; TABLES Tour; RUN;

22. The Levels You have already seen how to subset a dataset using the GUI and SQL. What if you want to subset into 3 different data sets? You could do a lot of pointing and clicking or write a little program.

25. That gets you only 1 of 3. That technique is not fun if you need to split into many subgroups. If you do need many subgroups, use code instead.

26. Splitting in a Data Step All data steps begin with the datastatement. Most have a set statement saying where the data is coming from, and they should end with a run statement. * A list of what data sets to make; data fj12 ps27 sh43; * based on what file? ; set day2.source; * Check the value of tour and if TRUE output; if tour = "FJ12"thenoutput fj12; if tour = "PS27"thenoutput ps27; if tour = "SH43"thenoutput sh43; return; * This line is optional; run;

27. What is a statement? • A statement is a single instruction beginning with a keyword and ending in a semicolon. • You can use white space and new lines to make them easier to read. • Look back at the proc sql statements you have seen and notice where the semicolons are. • SQL created table statements are LONG.

28. Parts of a SAS Dataset • You have seen how to browse a SAS dataset like a spreadsheet. There are two parts of a dataset which you do not see when you browse the data. • There is a section that acts like a dictionary which has a description of the data set, including among other things, the types of variables (character or numeric) and when the data set was created. • There is sometimes a section that has “index” information. You can create an index to help speed up processing of huge files.

29. Seeing the Details with EG

30. By Position Knowing the variables’ order can help you do complex things.

31. If want to code… • You can see the dictionary of attributes by typing a proc contents step in a code window: proccontentsdata=teletubbies; run; • To get the variables in their stored order, use: proccontentsdata=teletubbies position; run;

32. Formats and Labels • Formats and labels change the appearance of data but do not change the values. • Labels • Column headings in summaries • A way to deal with the fact that variables do not have spaces in the names • Formats • Add printing niceties like $ or , or Monday

33. Add Labels Deposit_date looks bad

36. Notice dates in Excel are actually the number of days since 1900 (in Windows). Dates in SAS are the number of days since 1960.

37. If you want to permanently change the format, use Filter and Query.

39. Custom Formats • You can write your own formats easily. • Say you want to show the size of the rental car needed to get people on a tour. • <=4 they need a normal car • 5-7 they need a minivan • 8+ they need a bus

41. Do not forget bad data.

42. Made but Useless The format is made but is not associated with any variable.

44. Make it look good. Be sure to label the format node in the flowchart and also link it up graphically to show where it is used.

45. Analysis of formatted data You can then use the formatted data for a categorical analysis without having to make new variables.

46. Diabetes Example Import an Excel file Describe the data Calculate BMI Do a t-test vs. a population BMI of 24.8