reclassifyCuts#

Purpose#

Replaces values of a matrix or array within specified ranges

Format#

x_new = reclassifyCuts(x, cut_pts[, close_right])#
Parameters:

  • x (NxK matrix or NxKxP array) – array to be recoded (changed)

  • cut_pts (Kx1 vector) – bounds of the specified ranges

  • close_right (Scalar) – optional argument, 1 if the cut_pts should be the right end-point of the interval, or 0 if the values in cut_pts should start the next interval. Default = 0.

Returns:

x_new (NxK matrix or NxKxP array) – Contains the recoded values of x, will have the same dimensions as the input x.

Examples#

Basic sequence#

// Create column vector to place in categories
x = {   0,
      0.1,
      0.2,
      0.3,
      0.4,
      0.5,
      0.6,
      0.7 };

// Cut points for data in 'x'
cut_pts = { 0.2,
            0.5 };

// Class 0:       x <= 0.2
// Class 1: 0.2 < x <= 0.5
// Class 2: 0.5 < x
r_open = reclassifyCuts(x, cut_pts);

// Class 0:       x < 0.2
// Class 1: 0.2 <= x < 0.5
// Class 2: 0.5 <= x
r_closed = reclassifyCuts(x, cut_pts, 1);

print "x = " x;
print;
print "r_open = " r_open;
print;
print "r_closed = " r_closed;
print;
print "cut_pts = " cut_pts;

After the code above:

x =
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70

r_open =
0.00
0.00
0.00
1.0
1.0
1.0
2.0
2.0

r_closed =
0.00
0.00
1.0
1.0
1.0
2.0
2.0
2.0

cut_pts =
0.20
0.50

Classifying blood pressure data#

// Create a column of blood pressure data
bp = {  87,
       154,
       127,
       112,
       159,
        90,
       151,
       109,
       125,
       107 };

// Assign cut points
cut_pts = { 120, 140 };

// Create categorical variable
bp_category = reclassifyCuts(bp, cut_pts);

print "bp = " bp;
print;
print "bp_category = " bp_category;
print;
print "cut_pts = " cut_pts;

After the code above:

      87
     154
     127
     112
bp = 159
      90
     151
     109
     125
     107

               0
               2
               1
               0
bp_category =  2
               0
               2
               0
               1
               0

cut_pts = 120
          140

We can take the categorical data output from reclassifyCuts() and use the reclassify() function to change the numeric categories to string categories like this:

// Starting categories
from = { 0, 1, 2 };

// New categories
to = "normal" $| "prehypertension" $| "hypertension";

bp_category = reclassify(bp_category, from, to);
print "bp_category = " bp_category;

After the code above:

              normal
              hypertension
              prehypertension
              normal
bp_category = hypertension
              normal
              hypertension
              normal
              prehypertension
              normal

Source#

datatran.src

See also

Functions code(), recode(), reclassify(), substute(), rescale()

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