/*--------------------------------------------------------------------* | Individual differences in color perception | | | | Normal and color-deficient subjects made similarity ratings by the | | method of triads on 10 Munsell color chips. | *--------------------------------------------------------------------*/ Title 'Individual Differences in Color Perception'; data helmraw; drop c1-c2 pair2; /* The data as given consist of interpoint distances for each ** pair of color chips for 16 'subjects'. The subjects ** CD DT ... JV are color deficient. NORMALS is the average ** data for ?? subjects with normal color vision. */ Input #1 C1 PAIR $2. CB DT MS RS NF1 JH RB1 CP JN #2 C2 PAIR2 $2. RW HG SW RB2 MG JV NORMALS; /* Each PAIR value gives the letter identifiers for the two color chips compared. */ Length Item1 Item2 $1; Item1= substr(PAIR,1,1); Item2= substr(PAIR,2,1); datalines; 1 AC 6.787 5.920 7.057 7.540 9.342 6.622 5.151 11.534 9.862 2 AC 6.216 7.475 5.991 5.759 9.030 9.245 10.351 6.120 1 AE 12.519 11.096 10.217 10.262 10.653 10.513 9.407 13.147 13.202 2 AE 10.843 9.079 9.370 10.515 9.985 10.836 12.409 10.501 1 AG 13.777 18.779 11.095 10.701 10.732 10.234 11.386 12.623 12.315 2 AG 9.907 10.177 9.518 13.383 10.403 9.747 12.786 12.054 1 AI 14.244 17.347 12.461 11.643 11.867 9.578 13.260 10.550 11.106 2 AI 11.145 12.147 9.543 13.983 9.952 10.073 13.695 13.114 1 AK 12.474 16.576 11.754 10.556 10.991 10.777 11.950 10.647 8.665 2 AK 10.334 12.533 9.792 13.161 9.305 10.267 11.849 12.368 1 AM 11.007 16.541 9.872 9.709 9.830 9.741 12.318 10.751 5.554 2 AM 8.814 9.721 8.679 11.664 8.596 9.739 4.298 10.621 1 AO 8.625 8.304 8.560 8.441 8.938 8.480 10.055 7.296 7.353 2 AO 7.601 9.763 6.727 10.182 8.764 8.959 4.041 8.481 1 AQ 5.486 5.742 4.297 5.775 8.888 4.943 4.881 5.386 6.389 2 AQ 5.759 8.298 4.949 6.352 7.523 6.614 5.490 5.184 1 AS 3.518 4.172 2.851 3.625 5.141 3.495 3.491 5.043 5.848 2 AS 3.018 6.664 4.129 3.472 5.848 4.647 4.067 3.133 1 CE 5.361 4.898 5.690 6.942 6.485 5.539 6.226 6.026 7.326 2 CE 7.509 4.397 7.053 4.904 6.852 5.451 8.105 5.469 1 CG 8.317 10.619 11.471 8.523 8.028 9.550 11.197 7.913 7.936 2 CG 8.885 7.890 9.490 12.162 8.896 8.236 10.821 9.864 1 CI 10.384 14.306 10.701 10.703 8.235 9.328 13.530 8.433 6.912 2 CI 10.712 10.394 9.529 14.798 8.405 9.397 10.387 11.611 1 CK 11.611 16.632 11.803 11.089 8.904 9.872 12.948 9.364 6.766 2 CK 10.828 11.230 9.862 14.602 8.286 10.134 4.593 12.394 1 CM 13.751 17.322 11.220 12.215 9.311 11.697 11.955 10.154 9.850 2 CM 10.565 12.568 10.582 14.110 9.673 10.498 9.620 12.983 1 CO 14.275 14.525 12.472 10.751 10.650 11.589 11.485 11.329 13.056 2 CO 10.445 11.414 10.570 13.445 11.085 10.824 12.302 12.454 1 CQ 11.760 9.498 9.235 9.885 10.067 10.315 8.234 11.530 12.736 2 CQ 9.002 11.265 8.490 9.708 10.626 11.172 14.213 9.914 1 CS 8.873 7.254 8.157 7.956 9.619 7.998 6.311 11.530 12.051 2 CS 7.512 10.442 7.876 7.944 10.315 10.484 12.984 8.025 1 EG 5.225 4.787 6.726 4.859 4.405 7.193 5.560 6.241 4.491 2 EG 6.252 5.659 7.614 4.626 5.974 4.554 3.475 5.428 1 EI 7.229 8.339 8.887 6.613 6.957 8.307 8.184 8.418 5.292 2 EI 8.721 8.251 8.918 8.271 6.812 6.665 4.251 8.105 1 EK 9.506 13.191 9.415 8.652 10.771 9.335 9.636 9.869 9.712 2 EK 9.624 10.236 9.806 10.694 8.227 9.846 7.866 10.068 1 EM 11.256 14.555 11.322 10.570 10.411 11.346 12.698 10.322 11.455 2 EM 10.136 11.274 10.537 12.778 10.889 11.258 13.013 12.097 1 EO 13.536 16.063 12.455 11.710 11.809 11.877 13.683 12.707 13.664 2 EO 10.782 12.184 10.716 14.054 11.554 11.865 13.830 13.109 1 EQ 14.577 13.985 11.940 11.102 11.638 11.819 13.373 12.854 14.095 2 EQ 11.663 11.895 9.687 12.902 9.601 11.470 14.813 12.816 1 ES 14.069 13.769 10.463 11.986 10.287 11.538 11.704 10.701 13.382 2 ES 9.383 10.655 10.155 10.890 10.482 10.213 13.865 11.829 1 GI 3.740 3.597 3.716 3.510 4.601 4.737 3.985 5.214 5.319 2 GI 3.883 3.875 3.837 3.546 4.206 3.663 3.548 3.346 1 GK 5.880 5.349 5.943 6.284 9.623 6.239 5.835 6.461 8.571 2 GK 6.830 6.473 5.299 4.705 7.269 6.580 8.966 5.490 1 GM 10.144 8.153 10.319 7.797 10.837 8.874 6.791 8.874 12.540 2 GM 9.448 8.667 7.326 8.820 10.086 8.662 12.349 8.538 1 GO 11.127 14.458 11.640 10.379 11.868 10.326 9.344 11.236 13.426 2 GO 9.740 10.305 7.625 11.044 10.248 10.557 12.291 10.569 1 GQ 12.330 16.982 10.865 11.633 11.272 11.623 10.459 11.697 14.102 2 GQ 10.383 10.735 9.177 11.802 10.604 9.980 12.941 12.070 1 GS 12.519 17.279 11.467 11.318 10.941 10.198 12.201 10.156 13.074 2 GS 9.668 12.558 10.114 11.747 10.324 7.674 14.462 12.389 1 IK 4.230 3.460 3.619 4.108 5.837 3.328 3.823 4.097 6.893 2 IK 4.954 4.600 4.750 3.589 5.190 4.005 6.994 3.450 1 IM 6.937 6.807 8.213 6.461 7.988 6.311 5.437 6.962 9.021 2 IM 8.271 7.758 6.242 6.869 7.622 7.514 13.053 6.510 1 IO 10.244 10.953 9.832 8.587 10.499 9.082 7.856 10.425 12.234 2 IO 8.975 9.901 8.156 9.385 9.214 9.942 13.101 9.309 1 IQ 12.104 15.777 11.265 10.028 10.412 11.067 9.893 10.801 12.495 2 IQ 10.948 11.210 9.121 12.439 10.315 10.931 13.618 11.630 1 IS 11.209 15.815 11.103 10.778 10.749 10.387 13.185 10.620 13.378 2 IS 9.600 11.623 9.734 13.685 10.345 10.585 14.062 12.119 1 KM 4.305 3.773 5.079 4.960 7.671 4.233 3.623 6.353 6.730 2 KM 4.314 6.268 4.720 4.072 6.402 5.429 9.949 4.122 1 KO 6.751 7.429 8.081 7.442 9.555 8.926 5.594 9.867 9.710 2 KO 7.334 9.559 6.673 6.868 9.469 9.331 11.300 7.295 1 KQ 9.905 13.750 10.223 9.105 10.640 9.413 8.953 9.422 11.253 2 KQ 9.035 10.643 8.769 10.567 9.972 9.934 13.625 10.151 1 KS 10.713 15.089 10.610 10.719 10.686 10.581 10.405 10.079 9.874 2 KS 8.839 11.573 9.875 12.204 9.558 9.717 12.291 11.521 1 MO 4.757 5.709 4.876 5.895 7.419 6.587 4.170 4.152 5.526 2 MO 4.916 4.788 4.478 4.149 7.001 5.579 3.866 4.531 1 MQ 7.443 10.911 8.716 8.677 8.990 8.878 8.205 8.367 7.408 2 MQ 7.158 6.803 7.226 10.034 7.862 8.206 5.269 8.348 1 MS 8.682 13.868 9.672 9.636 8.717 9.184 9.756 8.133 5.407 2 MS 7.600 9.045 6.775 11.051 8.697 9.650 6.362 9.363 1 OQ 4.454 4.970 6.349 5.625 5.531 5.835 5.099 4.546 4.242 2 OQ 4.728 4.550 4.000 4.113 4.794 5.300 4.735 4.477 1 OS 6.145 6.030 7.538 6.678 6.960 7.303 6.791 6.388 3.958 2 OS 5.638 7.403 5.269 6.884 6.710 6.290 3.167 6.213 1 QS 3.629 3.539 2.956 3.467 4.462 2.949 3.840 2.994 4.348 2 QS 3.466 5.215 3.369 3.397 4.321 3.410 2.362 2.963 ; /* transform the data to lower triangular similarity matrices */ proc transpose out=HTRANS1 name=SUBJ; data matrices; set HTRANS1; array col (45) col1-col45; drop col1-col45; t=0; DO x='A','C','E','G','I','K','M','O','Q','S'; DO STIM='A','C','E','G','I','K','M','O','Q','S'; if x>=STIM then dist=.; else do; t+1; if t<=45; dist=col(t); end; output; end; end; proc sort; by SUBJ STIM x; proc transpose out=HELM; var dist; id x; by SUBJ STIM; data HELM; set HELM; label subj='Subject'; drop _NAME_; proc print data=HELM (obs=30); by SUBJ; proc mds data=HELM level=INTERVAL model=INDSCAL pfinal out=CONFIG; matrix SUBJ; var A C E G I K M O Q S; run; Proc Format; Value $COLOR 'A'='RPur' /* reddish-purple */ 'C'='Red' 'E'='Yel' 'G'='Gy1' 'I'='Gy2' 'K'='Green' 'M'='Blue' 'O'='BlP' /* bluish-purple */ 'Q'='Pur1' 'S'='Pur2'; run; /* Separate the stimulus config from the subject weights */ Data STIM WEIGHTS; Set CONFIG; Drop SUBJ; Length ID $6; If _TYPE_='CONFIG' then do; ID = _NAME_; Output STIM; End; If _TYPE_='DIAGCOEF' then do; ID=SUBJ; Output WEIGHTS; End; proc print data=stim; proc print data=weights; proc plot data=stim; plot dim2 * dim1 $ id; format id $color.; proc plot data=weights; plot dim2 * dim1 $ id; run;