HOW TO USE THURSTONE CASE 5 (1)


An excellent discussion of Thurstone's Case 5 scaling is found in Green, P. E., D. S. Tull, and G.A. Albaum, Research for Marketing Decisions, Prentice Hall.
Thurstone's Case 5 scaling provides an algorithm for constructing a unidimensional interval scales from what is called comparative judgement measurement scales. Comparative judgement scales are exemplified by paired comparison statements such as "Stimulus 1 is preferable to Stimulus 2", or "I am more satisfied with product 1 than product 2". The interval scale values are generated from data that makes many repeated judgments on each pair of stimuli. A group of individuals may be used when there are no measurement replications for each person.

To illustrate the concept, consider a group of subjects who prefer brand 1 to brand 2. In this case, because brand 1 is preferred, the proportion of total comparisons in which brand 1 is preferred is near 100%. This situation is, however complicated when brand 2 is compared to brand 3. Suppose a smaller percentage, say 40%, prefer brand 2 to brand 3. The differences between preference of brand 1 to 2 and 2 to 3 would lead to the expectation that scale values for brands 1 and 2 would be greater than 2 and 3. Thurstone's Case 5 scaling provides a means for developing an interval scale from these proportions associated with comparative judgments.

Thurstone CASE 5 computes scale scores from

The basic reference for algorithm and test problems is:

Allen L. Edwards (1957), "Techniques of Attitude Scale Construction," New York, N.Y.: Appleton-Century-Crofts, Inc., pp. 33,42.


CASE 5 INPUT:

Line 1: PARAMETERS (Input in FREE Format)

1. Number of Respondents:

2. Number of Stimuli: Maximum = 60

3. Input Data Form:


Line 2: Input FORMAT describing the input data field

(80 columns maximum. F type format required)

DATA: DATA SET IS PLACED AFTER THE FORMAT STATEMENT

Lines 3: Labels (One line for each variable. Max=28 characters)

Lines 4 and 5: Titles (2 Lines, each up to 80 Characters wide)

When the scale graph is printed, variables are drawn on several different scales. Should you have multiple runs of a case on segmented data, it is possible upper limits may not be the same on each run and comparison might prove difficult. It is suggested that a common scale be selected for each segment and the other scales be discarded.


NOTES

1. An excellent discussion of Thurstone's Case 5 scaling is found in Green, P. E. and D. S. Tull Research for Marketing Decisions, Prentice Hall (1978), pp. 180-187.


CASE 5 SAMPLE DATA SET #1

In this example, we have 7 brands that are evaluated for preference using a paired comparisons task. The respondent was asked which brand they preferred... A or B for all of the possible brand combinations.

B1
B1
B1
B1
B1
B1
B2
B2
B2
B2
B2
B3
B3
B3
B3
B4
B4
B4
B5
B5
B6
Base - Total N
27
26
21
25
29
27
25
32
24
26
27
27
22
27
25
26
25
27
26
32
20
Brand 1  N
15
15
12
12
15
17
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Brand 1 Percent
56%
58%
57%
48%
52%
63%
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Brand 2 N
12
0
0
0
0
0
15
14
9
17
18
0
0
0
0
0
0
0
0
0
0
Brand 2 Percent
44%
-
-
-
-
-
60%
44%
38%
65%
67%
-
-
-
-
-
-
-
-
-
-
Brand 3 N
0
11
0
0
0
0
10
0
0
0
0
15
12
15
17
0
0
0
0
0
0
Brand 3 Percent
-
42%
-
-
-
-
40%
-
-
-
-
56%
55%
56%
68%
-
-
-
-
-
-
Brand 4 N
0
0
9
0
0
0
0
18
0
0
0
12
0
0
0
17
13
11
0
0
0
Brand 4 Percent
-
-
43%
-
-
-
-
56%
-
-
-
44%
-
-
-
65%
52%
41%
-
-
-
Brand 5 N
0
0
0
13
0
0
0
0
15
0
0
0
10
0
0
9
0
0
13
18
0
Brand 5 Percent
-
-
-
52%
-
-
-
-
63%
-
-
-
45%
-
-
35%
-
-
50%
56%
-
Brand 6 N
0
0
0
0
14
0
0
0
0
9
0
0
0
12
0
0
12
0
13
0
4
Brand 6 Percent
-
-
-
-
48%
-
-
-
-
35%
-
-
-
44%
-
-
48%
-
50%
-
20%
Brand 7 N
0
0
0
0
0
10
0
0
0
0
9
0
0
0
8
0
0
16
0
14
16
Brand 7 Percent
-
-
-
-
-
37%
-
-
-
-
33%
-
-
-
32%
-
-
59%
-
44%
80%

This data shows that 15 people (15/27=56%) preferred brand 1 over Brand 2 and 12 people (12/27=44%) preferred brand 2 over brand 1. These percentages are entered into a square data matrix with the diagonal values equal to .50.

 0.50 0.44 0.42 0.43 0.52 0.48 0.37 
 0.56 0.50 0.40 0.56 0.63 0.35 0.33
 0.58 0.60 0.50 0.44 0.45 0.44 0.32
 0.57 0.44 0.56 0.50 0.35 0.48 0.59
 0.48 0.38 0.55 0.65 0.50 0.50 0.44
 0.52 0.65 0.56 0.52 0.50 0.50 0.80
 0.63 0.67 0.68 0.41 0.56 0.20 0.50

The resulting data file appears:

 7  7  1  1  1  1
(7F5.2)
 0.50 0.44 0.42 0.43 0.52 0.48 0.37
 0.56 0.50 0.40 0.56 0.63 0.35 0.33
 0.58 0.60 0.50 0.44 0.45 0.44 0.32
 0.57 0.44 0.56 0.50 0.35 0.48 0.59
 0.48 0.38 0.55 0.65 0.50 0.50 0.44
 0.52 0.65 0.56 0.52 0.50 0.50 0.80
 0.63 0.67 0.68 0.41 0.56 0.20 0.50
Brand 1 Label
Brand 2 Label
Brand 3 Label
Brand 4 Label
Brand 5 Label
Brand 6 Label
Brand 7 Label
Scale:Overall Brand Preference
7 Brands

 

CASE 5 SAMPLE DATA SET #2

     10   05   02    1    1    1   
  (5F2.0)        
  0102030405     
  0504030201     
  0402010304     
  0302010405     
  0202020101     
  0303030302     
  0501010204     
  0502010204     
  0201030201     
  0102020204     
  VAR LABEL 1   
  VAR LABEL 2   
  VAR LABEL 3   
  VAR LABEL 4   
  VAR LABEL 5   
  SCALE TITLE LABEL
  SUB TITLE LABEL

CASE 5 SAMPLE OUTPUT

                THURSTONE CASE 5 
                PC-MDS VERSION 
  
 ANALYSIS TITLE: CASE5 TEST DATA
 DATA IS READ FROM FILE:    CASE5.DAT                              
 OUTPUT PRINT FILE IS:      CASE5.PRN                               
     NUMBER OF RESPONDENTS =   10. 
     NUMBER OF STIMULI     =    5 
     LOW LIMIT OF P        =     .0250 
     HIGH LIMIT OF P       =     .9750 
     INPUT IS RANKED DATA, COLUMNS REPRESENT STIMULI 
     (5F2.0)                                                                       
TALLY OF COMPARISONS 
    8.0   8.0   7.5   8.0   7.0   6.5   8.0   7.0   9.0   8.5 
  
  
FREQUENCY MATRIX - NUMBER OF TIMES STIMULUS (J) (COLUMN) 
PREFERRED OR RATED OVER STIMULUS (I) (ROW) 
              1         2         3         4         5 
     1       5.0000    8.0000    8.0000    7.5000    8.0000 
     2       2.0000    5.0000    7.0000    6.5000    8.0000 
     3       2.0000    3.0000    5.0000    7.0000    9.0000 
     4       2.5000    3.5000    3.0000    5.0000    8.5000 
     5       2.0000    2.0000    1.0000    1.5000    5.0000 
    SUMS    13.5000   21.5000   24.0000   27.5000   38.5000 

PROPORTION MATRIX - FREQUENCY MATRIX / NUMBER OF RESPONDENTS 
              1         2         3         4         5 
     1        .5000     .8000     .8000     .7500     .8000 
     2        .2000     .5000     .7000     .6500     .8000 
     3        .2000     .3000     .5000     .7000     .9000 
     4        .2500     .3500     .3000     .5000     .8500 
     5        .2000     .2000     .1000     .1500     .5000 
    SUMS      .8500    1.6500    1.9000    2.2500    3.3500 
          
THETA FOR P MATRIX 
              1         2         3         4 
     2      26.5650 
     3      26.5650   33.2108 
     4      29.9999   36.2711   33.2108 
     5      26.5650   26.5650   18.4349   22.7864 
  
     Z MATRIX -- STANDARD NORMAL DEVIATES CORRESPONDING TO 
     THE ENTRIES IN THE PROPORTION (P) MATRIX 

     **** INDICATES CORRESPONDING PROPORTION IS ABOVE THE HIGHER
	      LIMIT OR  BELOW THE LOWER LIMIT OF P 
               1         2         3         4         5 
     1        .0000     .8420     .8420     .6740     .8420 
     2       -.8420     .0000     .5240     .3850     .8420 
     3       -.8420    -.5240     .0000     .5240    1.2820 
     4       -.6740    -.3850    -.5240     .0000    1.0360 
     5       -.8420    -.8420   -1.2820   -1.0360     .0000 
    SUMS    -3.2000    -.9090    -.4400     .5470    4.0020 
          
    ZD (COLUMN DIFFERENCE) MATRIX 
    ENTRIES ARE DIFFERENCES BETWEEN THE INDICATED COLUMN ENTRIES OF THE Z MATRIX     
    **** INDICATES A MISSING ENTRY IN EITHER COLUMN OF THE Z MATRIX 
               2- 1      3- 2      4- 3      5- 4      
     1        .8420     .0000    -.1680     .1680 
     2        .8420     .5240    -.1390     .4570 
     3        .3180     .5240     .5240     .7580 
     4        .2890    -.1390     .5240    1.0360 
     5        .0000    -.4400     .2460    1.0360 
    SUMS     2.2910     .4690     .9870    3.4550 
  
    N         5         5         5         5 
  
    MEANS     .4582     .0938     .1974     .6910 
  
  
          *****FINAL SCALE VALUES***** 
    STIMULUS #         1         2         3         4         5 
    SCALE VALUE      .0000     .4582     .5520     .7494    1.4404 
    
    SCALE TITLE LABEL
    SUB TITLE LABEL
    NUMBER OF SUBJECTS=  10 
    
   1.45 - VAR LABEL 5
    .75 - VAR LABEL 4
    .55 - VAR LABEL 3
    .46 - VAR LABEL 2
    .00 - VAR LABEL 1                                                                                                              
    FINAL DRAWING ON   1.50  SCALE 
  
    SCALE TITLE LABEL
    SUB TITLE LABEL
    NUMBER OF SUBJECTS=  10 
  
   1.45 - VAR LABEL 5
    .75 - VAR LABEL 4  
	.55 - VAR LABEL 3                                                 
	.46 - VAR LABEL 2                                                 
	.00 - VAR LABEL 1                                                
	FINAL DRAWING ON   2.00  SCALE 
    SCALE TITLE LABEL
   SUB TITLE LABEL
   NUMBER OF SUBJECTS=  10 
  
   1.45 - VAR LABEL 5
    .75 - VAR LABEL 4
    .56 - VAR LABEL 3
    .46 - VAR LABEL 2
    .00 - VAR LABEL 1
                  
    FINAL DRAWING ON   2.50  SCALE 
  
    *****INTERNAL CONSISTENCY CHECK***** 
    DETERMINATION OF HOW WELL OBSERVED PROPORTION MATRIX (P) AGREES WITH 
    THEORETICAL PROPORTIONS (P-PRIME) CALCULATED FROM DERIVED SCALE VALUES 
  
    Z-PRIME MATRIX, - THEORETICAL NORMAL DEVIATES 
    CORRESPONDING TO SCALE VALUE DIFFERENCES 
              1         2         3         4 
     2       -.4582 
     3       -.5520    -.0938 
     4       -.7494    -.2912    -.1974 
     5      -1.4404    -.9822    -.8884    -.6910 
  
    P-PRIME MATRIX, - THEORETICAL PROPORTIONS, 
    CORRESPONDING TO Z-PRIME MATRIX ABOVE 
              1         2         3         4 
     2        .3230 
     3        .2900     .4620 
     4        .2260     .3850     .4210 
     5        .0740     .1620     .1870     .2440 

     THETA PRIME FOR P PRIME MATRIX 
              1         2         3         4 
     2      34.6338 
     3      32.5826   42.8206 
     4      28.3850   38.3514   40.4545 
     5      15.7850   23.7340   25.6221   29.6014 
  
     CHI SQ =     5.7904     Z VALUE =      .0864 
  
     DISCREPANCY MATRIX, -- "P" MINUS "P-PRIME" 
              1         2         3         4 
     2       -.1230 
     3       -.0900    -.1620 
     4        .0240    -.0350    -.1210 
     5        .1260     .0380    -.0870    -.0940 
    SUMS      .3630     .2350     .2080     .0940 

      N         4         3         2         1 
     AVERAGE DISCREPANCY =    .0900