SAS Macro Programs: slice

The slice macro ( get slice.sas)

Divide a variable into slices, allowing overlap

The SLICE macro divides the values of a variable into subranges or slices for use in conditioning plots (coplots or ccmaps). If the variable is character, each distinct value is a slice. Otherwise, the range of the variable is divided into SLICE= ranges, allowing each successive pair to overlap by a fraction, OVERLAP=, so a given observation can appear in more than one slice. In conditioning plots, this helps to smooth the conditioning variable(s).

The result is an output OUT= data set containing an additional variable, SLICEVAR= giving the slice value for each observation (which may appear 1 or 2 times).

Usage

The SLICE macro is defined with keyword parameters. The arguments may be listed within parentheses in any order, separated by commas. For example:

   %slice(data=test, var=x, slices=5);

Parameters

DATA=

The name of the input data set

VAR=

The name of the variable to be sliced

SLICES=

Number of slices (if VAR is numeric) [Default: SLICES=4]

OVERLAP=

Overlap between adjacent slices (numeric) [Default: OVERLAP=.25]

OUT=

The name of the output data set [Default: OUT=_EXPAND_]

OUTS=

Name of output slice data set. This contains one observation per slice, with the upper/lower values and upper/lower percents of observations in each slice. [Default: OUTS=_SLICES_]

SLICEVAR=

Name for slice variable [Default: SLICEVAR=SLICE]

Example

%include macros(slice);        *-- or include in an autocall library;
  data test;
     drop i;
     do group='A1', 'A2';
      do i=1 to 5;
          x = int(50 + 25 * normal(12424241));
          output;
      end;
     end;
  run;

  %slice(data=test, var=x, out=nout, slices=5);
  proc print data=nout;
  proc print data=_slices_;

Produces:

 Obs    slice    lowerx    upperx    n    group       x

  1      1         -6        28     3     A2        -6
  2      1         -6        28     3     A2        23
  3      1         -6        28     3     A1        28
  4      2         28        31     2     A1        28
  5      2         28        31     2     A2        31
  6      3         43        53     2     A1        43
  7      3         43        53     2     A1        53
  8      4         76        77     2     A2        76
  9      4         76        77     2     A1        77
 10      5         92       110     2     A1        92
 11      5         92       110     2     A2       110

and, the _slices_ data set:

 Obs    slice    lowerx    upperx    n     lopct      uppct

  1       1         -6        28     3     0.0000     29.310
  2       2         28        31     2    29.3103     31.897
  3       3         43        53     2    42.2414     50.862
  4       4         76        77     2    70.6897     71.552
  5       5         92       110     2    84.4828    100.000

See also