- PROC TABULATE creates customized tables that display descriptive statistics from SAS data. It allows users to classify and analyze variables to produce one, two, or three-dimensional tables. - The procedure uses CLASS, VAR, and TABLE statements to specify how variables should be classified, analyzed, and presented in the table. Common statistics like frequency, mean, sum can be calculated and displayed. - Two-way and multi-dimensional tables can be created to examine relationships between multiple variables. Formatting and summary options provide flexibility in customizing table output.

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8. SAS Techies 2009 TABLE page-expression, row-expression, column-expression ; Dimension expressions contain elements . Dimension expressions can also contain operators that you use when combining elements to produce the table you want. Commas , one type of operator, separate the dimensions of the table. 11/13/09

13. SAS Techies 2009 To group elements and control how expressions are evaluated, you can use the parentheses operator. You can also produce hierarchical tables by using the asterisk operator to cross class variables with other variables. concatenation, using the blank Operator to display variables side by side or stacked 11/13/09 table height*mean weight*mean,sex all; table sex,actlevel*age*max; table type*(sex all);

14. SAS Techies 2009 You can condense multiple pages into a single page. Condensed output You can specify how percentages are calculated. You can create formats to change headings for class variable values. 11/13/09 table type,fee,sum / condense ; table type,fee*sex*pctsum<type>; proc format; value $actfmt 'LOW'='(1) Low' 'MOD'='(2) Moderate' 'HIGH'='(3) High';

15. SAS Techies 2009 11/13/09 Error How to rectify VARIABLE appears in both CLASS and VAR lists. You specified a variable as both class and analysis. Type of name (VARIABLE) unknown at line n. You forgot to specify a variable as either class or analysis. Variable VARIABLE in list does not match type prescribed for this list. You specified a character variable as analysis.

22. SAS Techies 2009 levels v tables sex*weight*height ; ^ ^ rows + columns = two-way tables proc freq data=clinic.diabetes; tables sex*weight*height ; format weight weight. height height.; run; 11/13/09 Frequency Percent Row Pct Col Pct Table 1 of Weight by Height Controlling for Sex=F Weight Height Total < 5'5&quot; 5'5-10&quot; > 5'10&quot; < 140 2 18.18 100.00 28.57 0 0.00 0.00 0.00 0 0.00 0.00 . 2 18.18 140-180 5 45.45 55.56 71.43 4 36.36 44.44 100.00 0 0.00 0.00 . 9 81.82 > 180 0 0.00 . 0.00 0 0.00 . 0.00 0 0.00 . . 0 0.00 Total 7 63.64 4 36.36 0 0.00 11 100.00 Frequency Percent Row Pct Col Pct Table 2 of Weight by Height Controlling for Sex=M Weight Height Total < 5'5&quot; 5'5-10&quot; > 5'10&quot; < 140 0 0.00 . . 0 0.00 . 0.00 0 0.00 . 0.00 0 0.00 140-180 0 0.00 0.00 . 1 11.11 100.00 25.00 0 0.00 0.00 0.00 1 11.11 > 180 0 0.00 0.00 . 3 33.33 37.50 75.00 5 55.56 62.50 100.00 8 88.89 Total 0 0.00 4 44.44 5 55.56 9 100.00