-
$BDj<02=(B :
-
$B?HD9!"BN=E!"6;0O$G$NAm9g;XI8$r5a$a$F$_$h$&(B :
- SAS$B%W%m%0%i%`(B : PCA0702.sas
- $B=PNO7k2L(B : SAS_out0702a.txt
, Results_PCA0702.pdf
- $B3FJQNL$NJ?6Q!"I8=`JP:9!"6&J,;69TNs(B
- $B8GM-CM!"HfN((B($B4sM?N((B)$B!"N_@Q4sM?N((B
- $B8GM-%Y%/%H%k(B
- $B $BBh(B1$B<4!ABh(B3$B<4$N;6I[?^(B
Monday, November 16, 2020 10:39:12 PM 39
The PRINCOMP Procedure
Observations 157
Variables 3
Simple Statistics
shintyou taijyuu kyoui
Mean 168.9630573 60.29745223 85.87961783
StD 8.2893064 10.56333128 9.08721093
Covariance Matrix
shintyou taijyuu kyoui
shintyou 68.7126008 59.4152899 19.1188576
taijyuu 59.4152899 111.5839678 42.4632811
kyoui 19.1188576 42.4632811 82.5774024
Total Variance 262.87397109
Eigenvalues of the Covariance Matrix
Eigenvalue Difference Proportion Cumulative
1 175.861980 113.969485 0.6690 0.6690
2 61.892495 36.772999 0.2354 0.9044
3 25.119496 0.0956 1.0000
Monday, November 16, 2020 10:39:12 PM 40
The PRINCOMP Procedure
Eigenvectors
Prin1 Prin2 Prin3
shintyou 0.494028 -.430097 0.755614
taijyuu 0.748683 -.231424 -.621222
kyoui 0.442053 0.872616 0.207677
Monday, November 16, 2020 10:39:13 PM 41
s
h t k c
i a j o a t
n i k i d r s P P P
t j y t u r u r r r
O s y y o a k y u i i i
b e o u u k a e w n n n
s x u u i u i r a 1 2 3
1 F 146.7 41.0 85 $B<+Bp@8(B 10000 Vodafone 6000 -25.8351 13.2736 -5.0170
2 F 148.0 43.0 80 $B<+Bp@8(B 50000 DoCoMo 4000 -25.9057 7.8885 -6.3155
3 F 150.0 46.0 86 40000 . -20.0193 11.5698 -5.4219
4 F 151.7 41.5 80 $B<+Bp@8(B 35000 . -25.2009 6.6443 -2.5879
5 F 152.0 35.0 77 $B<+Bp@8(B 60000 DoCoMo 2000 -31.2452 5.4017 1.0537
6 F 153.0 46.5 87 $B2<=I@8(B 10000 . -17.7208 11.0364 -3.2580
7 F 153.0 55.0 78 $B<+Bp@8(B 30000 . -15.3355 1.2157 -10.4074
8 F 154.4 44.0 75 $B<+Bp@8(B 9000 au 2000 -24.2055 0.5414 -3.1392
9 F 155.0 48.0 83 $B2<=I@8(B 180000 . -17.3780 6.3386 -3.5093
10 F 156.0 42.0 85 $B<+Bp@8(B 0 DoCoMo 15000 -20.4919 9.0423 1.3890
11 F 156.0 46.0 82 $B<+Bp@8(B 10000 Vodafone 7000 -18.8234 5.4987 -1.7189
12 F 156.0 48.0 70 $B<+Bp@8(B 30000 . -22.6306 -5.4355 -5.4534
13 F 156.0 49.0 85 $B<+Bp@8(B 25000 . -15.2512 7.4223 -2.9595
14 F 156.0 50.0 82 $B<+Bp@8(B 40000 Vodafone 10000 -15.8286 4.5730 -4.2038
15 M 156.0 61.0 90 $B<+Bp@8(B 0 . -4.0567 9.0083 -9.3758
Monday, November 16, 2020 10:39:13 PM 42
Plot of Prin2*Prin1. Legend: A = 1 obs, B = 2 obs, etc.
20 + |
| |
| A | A A A
| A A |
| A A A AA AA | A B A A
| A A AAADC A B A| AAA A
| AAA AAAB DAB CAB F AA AAB AA A
0 +-----------A-----B-BB---A-AA+-BB--CCCC-AA--A-A------A------------------
| A B C ABC ADA BA
| A A AACA B B A A
Prin2 | B A B A A A
| A A A A
| A |
| A |
-20 + |
| A |
| |
| |
| |
| |
| |
-40 + |
| |A
| |
| A |
| |
| |
| |
-60 + |
-+-------------+-------------+-------------+-------------+-------------+
-40 -20 0 20 40 60
Prin1
Monday, November 16, 2020 10:39:13 PM 43
Plot of Prin3*Prin2. Legend: A = 1 obs, B = 2 obs, etc.
20 + |
| |
| |
| |
| |
| |
| A A
10 + A A |
| A BA |
| A A AB |
Prin3 | BAA AAA | A A
| A BA A AD A A
| A B AAABDAA A
| A A AA A|BEBAA AAA A
0 +-----------------------------------------B-AB---AA+ABF-CAABB-----A-----
| A AA|C ACAAA
| A AAA ABBC AAAB A A A
| ABBAA AB
| AA A A A A AA
| AA A
| | A
-10 + |A A
| A |
| | A
| A |
| A
| |
| |
-20 + A |
-+---------+---------+---------+---------+---------+---------+---------+
-50 -40 -30 -20 -10 0 10 20
Prin2
Monday, November 16, 2020 10:39:13 PM 44
Plot of Prin3*Prin1. Legend: A = 1 obs, B = 2 obs, etc.
20 + |
| |
| |
| |
| |
| |
| A A
10 + A | A
| | A B A
| A A A B
Prin3 | A AD A B
| AAB A| BA AA B
| AA B B AB BB A A
| A AA C ABB B|A C A A A
0 +---------------AA-ABBAAAA-A-A-AB-AA-C-BBA------------------------------
| AB BB A A| AAA A
| AA ABA B AAA BAAAA B A
| A A A A | A ABA A
| B A A A A | A A
| |A A A
| | A
-10 + A A |
| A |
| | A
| | A
| | A
| |
| |
-20 + |A
-+-------------+-------------+-------------+-------------+-------------+
-40 -20 0 20 40 60
Prin1
- $B2r
- $B4sM?N((B : 2$B<4$^$G $B3F<4$N0UL#IU$1(B
- $BBh(B1$B<4(B : $BA4BNE*$JBN3J$N0x;R!#FC$KBN=E$,8z$$$F$$$k!#(B
- $BBh(B2$B<4(B : $BB@$5$N0x;R(B(?)$B!#6;0O$,@5$GBg$-$/!"?HD9$,Ii!#(B
- $B$A$J$_$K!"Bh(B3$B<4(B : $B2ZTz$5$N0x;R(B(?)$B!#L5;k$7$F$bNI$$<4$G$"$k$,!#(B(9.6%)$B!#(B
$BAj4X9TNs$r;H$&M}M3(B
- $BJQNL$K$h$C$FB,DjC10L$,0[$J$k(B
- $B;H$&C10L$K$h$C$F2r@O7k2L$,0[$J$k(B
- $BJ,;6$N1F6A$r $B3FJQNL$rI8=`2=$7$FMQ$$$k(B : $BAj4X9TNs(B <===> $BJ,;66&J,;69TNs(B
- $BAj4X9TNs$rMQ$$$FBN3J$NAm9g;XI8$r5a$a$F$_$h$&(B :
- SAS$B%W%m%0%i%`(B : PCA0703.sas
- $B=PNO7k2L(B : SAS_out0703a.txt
, Results_PCA0703.pdf
- $B3FJQNL$NJ?6Q!"I8=`JP:9!"Aj4X9TNs(B
- $B8GM-CM!"HfN((B($B4sM?N((B)$B!"N_@Q4sM?N((B
- $B8GM-%Y%/%H%k(B
- $B $BBh(B1$B<4!ABh(B3$B<4$N;6I[?^(B
Monday, November 16, 2020 10:41:50 PM 54
The PRINCOMP Procedure
Observations 157
Variables 3
Simple Statistics
shintyou taijyuu kyoui
Mean 168.9630573 60.29745223 85.87961783
StD 8.2893064 10.56333128 9.08721093
Correlation Matrix
shintyou taijyuu kyoui
shintyou 1.0000 0.6785 0.2538
taijyuu 0.6785 1.0000 0.4424
kyoui 0.2538 0.4424 1.0000
Eigenvalues of the Correlation Matrix
Eigenvalue Difference Proportion Cumulative
1 1.93952761 1.16742579 0.6465 0.6465
2 0.77210183 0.48373127 0.2574 0.9039
3 0.28837056 0.0961 1.0000
Monday, November 16, 2020 10:41:50 PM 55
The PRINCOMP Procedure
Eigenvectors
Prin1 Prin2 Prin3
shintyou 0.597004 -.504531 0.623727
taijyuu 0.651546 -.148678 -.743897
kyoui 0.468053 0.850496 0.239964
- $B2r
- $B4sM?N((B : 2$B<4$^$G $B3F<4$N0UL#IU$1(B
- $BBh(B1$B<4(B : $BA4BNE*$JBN3J$N0x;R!#(B
- $BBh(B2$B<4(B : $BB@$5$N0x;R!#(B
- [$B:#2sNc$G$O(B] $BJ,;66&J,;69TNs$r;H$C$?$H$-$h$j$b(B
$BBh(B1$B<4$N8GM-%Y%/%H%kF1;N$,6a$$CM$K$J$C$?!#$7$+$7!"<4$N2r
$B!Z;29M![J,;66&J,;69TNs$HAj4X9TNs$r;H$C$?$H$-$N0c$$$r8+$F$_$?$1$l$P!"(B
shintyou $B$N$_$r(B mm $BC10L$GB,Dj$7$?$H2>Dj$7$F!"(B
10$BG\$7$?$b$N$r%G!<%?$H$7$FN>
- SAS$B%W%m%0%i%`(B : PCA0704.sas
- $B=PNO7k2L(B : SAS_out0704a.txt
, Results_PCA0704.pdf
$B
$BL@3N$K7h$^$C$F$$$k$o$1$G$O$J$$$,!"0J2<$N$h$&$J4p=`$,0lHLE*$K(B
$BMQ$$$i$l$F$$$k!#$^$?!"7k2L$N2re!"B?>/A}8:$5$;$k$3$H$b$"$k!#(B
- $BN_@Q4sM?N($,$"$kDxEY(B($BNc$($P(B80%$B0J>e(B)$B0J>eBg$-$/$J$k$3$H(B
- $B8GM-CM$N%.%c%C%W$,$"$kDxEY0J>eBg$-$$$3$H(B
- $BAj4X9TNs$rMQ$$$F$$$k>l9g!"8GM-CM$,(B 1$B0J>e(B
- ...
[$B%N%&%O%&(B] $B<4$NFC@-$rGD0.$9$k$K$O%i%$%s%^!<%+!<$,=EJu$9$k!#(B $B0l$D$N<4Fb$GBg$-$$(B($B$b$7$/$O>.$5$$(B)$B8GM-%Y%/%H%k$K%^!<%/$9$k$H!"(B $B2?$,%0%k!<%T%s%0$5$l$F$$$k$+$,M}2r$70W$/$J$k!#(B $B$?$@!":#=5$NNc<($G$O(B3$B<4$^$G$7$+=P8=$7$J$$$N$G!"$4Mx1W$O46$8$K$/$$$H$b;W$&!#(B $BB?JQNL(B($BNc$($P0J2<$NNcBj(BPCA/FA)$B$K$J$l$P$=$NM-8z@-$,M}2r$G$-$k$G$"$m$&!#(B
[$BNcBj(BPCA] $B?)IJ$NSO9%@-$rC5$C$F$_$h$&(B
100$B.$5$$J}$+$i=g$K(B 15$B:M0J2e$N(B10$B72$r9=@.$7$F$$$k!#(B $B$^$?!"B,Dj<\EY$O!V(B1: $B$*$i$/?)$Y$k5$$,$7$J$$!W!"!V(B2: $B$b$76/@)$5$l$l$P?)$Y$k!W!"!D!"(B $B!V(B8: $B$$$D$b?)$Y$?$$!W!"!V(B9: $B$b$C$H$b9%$-$J?)IJ$KF~$k!W$^$G$N(B9$BCJ3,$G$"$j!"(B $B3F%0%k!<%W$4$H$K<\EY$NJ?6QCM$r
- $BAj4X9TNs$rMQ$$$FAm9g;XI8$r5a$a$F$_$h$&(B :
- SAS$B%W%m%0%i%`(B : PCA0705.sas
- $B=PNO7k2L(B : SAS_out0705a.txt
, Results_PCA0705.pdf
Thursday, November 19, 2020 12:34:23 PM 75
Obs X01 X02 X03 X04 X05 X06 X07 X08 X09 X10
1 7.69 7.31 7.47 7.76 7.87 7.51 7.24 7.70 7.91 7.95
2 6.59 5.56 6.21 6.04 5.81 6.64 6.11 6.53 6.44 6.64
3 4.55 4.18 4.36 4.25 4.53 4.60 3.66 4.04 3.68 4.43
4 6.78 6.11 6.30 5.98 5.56 6.37 6.29 5.43 5.32 5.28
5 6.47 6.24 6.02 5.42 5.88 6.00 5.60 4.60 5.40 5.95
6 6.96 6.81 6.91 6.48 6.23 7.09 7.27 7.13 6.86 7.36
7 6.57 5.70 5.89 5.16 5.30 6.07 5.56 4.50 4.92 5.33
8 7.32 6.95 6.02 4.98 4.88 6.82 6.40 5.53 5.61 5.33
9 6.51 6.15 5.51 4.68 4.16 5.17 4.81 4.70 4.86 3.82
10 6.86 6.05 5.85 6.14 6.75 6.71 5.39 5.42 6.03 6.59
Thursday, November 19, 2020 12:34:23 PM 76
The PRINCOMP Procedure
Observations 100
Variables 10
Simple Statistics
X01 X02 X03 X04 X05
Mean 6.038100000 5.784800000 5.947100000 5.669500000 5.640600000
StD 1.239147389 1.034139939 0.825972699 0.915395124 0.884228614
Simple Statistics
X06 X07 X08 X09 X10
Mean 5.781300000 5.563900000 5.379400000 5.517400000 5.542100000
StD 1.294327683 1.182607883 1.121124814 1.016264322 1.130856737
Correlation Matrix
X01 X02 X03 X04 X05
X01 M(-15) 1.0000 0.8708 0.5158 0.3701 0.1723
X02 M(16-20) 0.8708 1.0000 0.7588 0.6043 0.4021
X03 M(21-30) 0.5158 0.7588 1.0000 0.8524 0.7262
X04 M(31-40) 0.3701 0.6043 0.8524 1.0000 0.8742
X05 M(41-) 0.1723 0.4021 0.7262 0.8742 1.0000
X06 F(-15) 0.9384 0.8207 0.5164 0.3580 0.2077
X07 F(16-20) 0.8107 0.8381 0.6584 0.4875 0.3543
X08 F(21-30) 0.6161 0.7095 0.6990 0.6199 0.5235
X09 F(31-40) 0.5003 0.6470 0.7013 0.7207 0.7101
X10 F(41-) 0.3298 0.4569 0.5584 0.6321 0.7479
Thursday, November 19, 2020 12:34:23 PM 77
The PRINCOMP Procedure
Correlation Matrix
X06 X07 X08 X09 X10
X01 0.9384 0.8107 0.6161 0.5003 0.3298
X02 0.8207 0.8381 0.7095 0.6470 0.4569
X03 0.5164 0.6584 0.6990 0.7013 0.5584
X04 0.3580 0.4875 0.6199 0.7207 0.6321
X05 0.2077 0.3543 0.5235 0.7101 0.7479
X06 1.0000 0.8888 0.7465 0.6215 0.4932
X07 0.8888 1.0000 0.8949 0.7679 0.6415
X08 0.7465 0.8949 1.0000 0.8528 0.7741
X09 0.6215 0.7679 0.8528 1.0000 0.9112
X10 0.4932 0.6415 0.7741 0.9112 1.0000
Eigenvalues of the Correlation Matrix
Eigenvalue Difference Proportion Cumulative
1 6.82795512 5.06608201 0.6828 0.6828
2 1.76187311 1.00742187 0.1762 0.8590
3 0.75445124 0.49207487 0.0754 0.9344
4 0.26237637 0.14082435 0.0262 0.9607
5 0.12155202 0.02358655 0.0122 0.9728
6 0.09796547 0.02586580 0.0098 0.9826
7 0.07209967 0.02801926 0.0072 0.9898
8 0.04408041 0.00832792 0.0044 0.9942
9 0.03575249 0.01385842 0.0036 0.9978
10 0.02189408 0.0022 1.0000
Thursday, November 19, 2020 12:34:23 PM 78
The PRINCOMP Procedure
Eigenvectors
Prin1 Prin2 Prin3 Prin4 Prin5
X01 M(-15) 0.286033 -.446335 0.193512 0.428019 0.162365
X02 M(16-20) 0.331337 -.239842 0.336063 0.022488 -.559594
X03 M(21-30) 0.323345 0.166337 0.442291 -.436029 -.168594
X04 M(31-40) 0.299329 0.358627 0.375366 0.063449 0.367912
X05 M(41-) 0.260727 0.507209 0.127419 0.375425 0.146879
X06 F(-15) 0.308635 -.407882 -.083695 0.267375 0.286866
X07 F(16-20) 0.344271 -.252697 -.171400 -.295655 -.025050
X08 F(21-30) 0.347877 -.032314 -.289087 -.507508 0.452377
X09 F(31-40) 0.345636 0.164368 -.322236 0.040012 -.388944
X10 F(41-) 0.303334 0.267273 -.522559 0.251270 -.190507
Eigenvectors
Prin6 Prin7 Prin8 Prin9 Prin10
X01 -.016413 -.062138 -.038493 -.141617 0.668052
X02 -.212367 0.479465 0.283325 -.013739 -.225064
X03 0.476929 -.416354 0.136150 0.085922 0.163960
X04 -.562491 -.066245 -.114301 0.403713 -.068344
X05 0.385123 0.325310 -.167534 -.437833 -.148648
X06 0.209878 -.335058 0.176137 0.090538 -.618107
X07 0.137469 0.236104 -.762654 0.204382 -.046351
X08 -.128390 0.256135 0.382983 -.303270 0.106863
X09 -.387189 -.488821 -.161974 -.425188 -.030381
X10 0.181955 0.100632 0.270185 0.543107 0.229904
Thursday, November 19, 2020 12:34:24 PM 79
Obs X01 X02 X03 X04 X05 X06 X07 X08 X09 X10 Prin1 Prin2
1 7.69 7.31 7.47 7.76 7.87 7.51 7.24 7.70 7.91 7.95 5.88693 1.44204
2 6.59 5.56 6.21 6.04 5.81 6.64 6.11 6.53 6.44 6.64 1.65842 0.13686
3 4.55 4.18 4.36 4.25 4.53 4.60 3.66 4.04 3.68 4.43 -4.44537 -0.34692
4 6.78 6.11 6.30 5.98 5.56 6.37 6.29 5.43 5.32 5.28 0.72138 -0.63217
5 6.47 6.24 6.02 5.42 5.88 6.00 5.60 4.60 5.40 5.95 0.15339 -0.18363
6 6.96 6.81 6.91 6.48 6.23 7.09 7.27 7.13 6.86 7.36 3.65322 0.09908
7 6.57 5.70 5.89 5.16 5.30 6.07 5.56 4.50 4.92 5.33 -0.65902 -0.78995
8 7.32 6.95 6.02 4.98 4.88 6.82 6.40 5.53 5.61 5.33 0.76044 -1.96919
9 6.51 6.15 5.51 4.68 4.16 5.17 4.81 4.70 4.86 3.82 -1.96687 -1.71968
10 6.86 6.05 5.85 6.14 6.75 6.71 5.39 5.42 6.03 6.59 1.35649 0.51749
11 7.04 6.03 6.53 6.02 6.68 6.78 5.91 6.26 5.76 5.95 1.76317 0.15476
12 6.59 6.30 6.29 5.94 6.10 5.93 5.52 5.35 5.45 5.85 0.72383 0.14551
13 5.93 4.76 5.09 5.51 5.79 5.49 4.97 4.69 5.30 5.61 -1.20892 0.34668
14 7.00 6.31 6.82 6.26 5.26 6.69 6.27 5.94 5.78 5.26 1.42272 -0.75706
15 6.63 5.47 5.54 4.88 4.70 5.89 4.64 4.43 4.00 3.98 -2.13183 -1.49511
Obs Prin3 Prin4 Prin5 Prin6 Prin7 Prin8 Prin9 Prin10
1 -0.07682 0.40809 0.25348 -0.08404 0.00629 0.07518 -0.29432 0.07804
2 -0.90098 -0.05516 0.42231 -0.06712 -0.42537 0.15924 0.03126 0.21633
3 -0.55169 0.23782 0.37097 0.08301 0.22924 0.36927 0.13546 -0.13545
4 0.55357 -0.08449 0.21583 0.10836 -0.04069 -0.30130 0.23414 0.03747
5 0.21693 0.67993 -0.55569 0.43975 0.12407 -0.03449 0.20098 0.03292
6 -0.63902 -0.35301 -0.06665 0.08296 0.01967 0.09429 0.27099 0.10991
7 0.26301 0.42015 -0.16052 0.48267 -0.13359 -0.13508 0.28383 0.14238
8 0.06701 -0.04720 -0.60733 0.05720 0.07830 0.10980 -0.04606 0.07099
9 0.66740 -0.33431 -0.54215 -0.50605 -0.09164 0.28167 -0.34880 0.33721
10 -0.17674 1.31452 0.21057 0.17171 0.08563 0.18324 -0.13665 -0.09062
11 0.23456 0.33063 0.60092 0.58481 0.05801 0.16376 -0.43135 0.07070
12 0.49777 0.35538 -0.09548 0.21636 0.19362 0.18252 0.04441 0.14858
13 -0.53251 0.85212 0.41764 -0.06351 -0.06122 -0.26835 -0.02047 0.09838
14 0.71704 -0.53272 0.19744 -0.12540 -0.54510 0.00683 0.21138 0.12406
15 0.88751 0.23480 0.36191 0.24293 -0.09797 0.25997 0.00113 0.14547
Thursday, November 19, 2020 12:34:24 PM 80
Plot of Prin2*Prin1. Legend: A = 1 obs, B = 2 obs, etc.
4 + |
| |
| |
| |
| |
| A A|
| |A A
2 + A | A A A
| A A A A
| |A A A A
Prin2 | A A A B| A A
| A B AA A| A A
| A A A A AA A A B
| A A A A A | A A A A
0 +----------------------------------A----A+--A----A---A-----AA-------A---
| A A |A A A
| A A A | A BA A
| A A | A B AA
| A | A A
| A | A A A
| A A A | A A
-2 + A A A| A
| A | A A
| A |
| | A
| |
| |
| A |
-4 + |
-+---------+---------+---------+---------+---------+---------+---------+
-8 -6 -4 -2 0 2 4 6
Prin1
Thursday, November 19, 2020 12:34:24 PM 81
Plot of Prin3*Prin2. Legend: A = 1 obs, B = 2 obs, etc.
Prin3 | |
| |
3 + |
| | A
| |
| | A
| A | A
2 + | A
| | A
| | A
| | AA
| A |
1 + | AA
| AA AAA |
| A A A | A
| A A |A A
| A A A A AA BBA AA A A AA A A
0 +-------------------AA-A-A-A-------------+-------------A----------------
| A A AAA | A AA A
| A A A A A A A AA
| A A B |B A A A A B A
| B A | A A A
-1 + A AAA B A A
| |
| | A A A
| | AA
| |
-2 + |
| |
-+---------+---------+---------+---------+---------+---------+---------+
-4 -3 -2 -1 0 1 2 3
Prin2
- $B2r -->
- $B4sM?N((B : 2$B<4$^$G $B$7$+$7!"8GM-CM$NJQ2=NL$+$i$9$k$H!"(B3$B<4$G$bNI$5$=$&(B : 3$B$H(B4$B$N4V$,6u$$$F$k$+$i(B
- $B $B3F<4$N0UL#IU$1(B: $B;29M$^$G$K(B$B?)IJHV9f$G%W%m%C%H(B$B$7$F$_$k$H!#(B
- $BBh(B1$B<4(B : $BA4BNE*$JSO9%EY9g$$!#(B
- $BBh(B2$B<4(B : $BG/Np$K$h$kSO9%EY9g$$(B($B $BBh(B3$B<4(B : $B@-JL$K$h$kSO9%EY9g$$(B($BCK@-$@$H%W%i%9(B)$B!#(B
$B0x;RJ,@O(B: $B%b%G%k(B
$B!!>e=R$Nl9g$O!"(B
$B%G!<%?$N;6$i$P$jJ}(B($BJ,;6(B)$B$rB*$($F%G!<%?FC@-$rGD0.$9$k/$7M}2r$7$K$/$$$+$b$7$l$J$$$,(B)$B!#(B
$B$3$N
- $BDj<02=(B
-
$BNc$($P!"(Bi$BHVL\$N3X@8$N(B3$B2JL\$N;n83@.@S(B 
$B$,F@$i$l$F$$$?$H$9$k(B(i=1,2,$B!D(B,n)$B!#(B fi$B$r(Bi$BHVL\$N3X@8$NFCD'$rI=$9MWAG!"(Baj$B$r(Bj$BHVL\$N2JL\$NFCD'$rI=$9MWAG$H$7!"(B $B$=$l$i$,0J2<$N$h$&$J@Q$N7A$GI=8=$G$-$?$H$7$?$i!"3X@88D?M$H2JL\$NFC@-$,J,N%$G$-$k$3$H$K$J$k!#(B
-
-
$B$3$3$G!"(B
-
$BB,DjBP>](B
: $B@.@S!"B,DjCM!"!D!#(B
-
$B6&DL0x;R(B($B@x:_JQNL(B) :
: $B0x;RF@E@(B($BB,DjITG=(B)$B!"8DBN$NFCD'IU$1!";6I[?^$K!"(Bi=1,2,3,$B!D(B,n.
-
$B0x;RIi2YNL(B($B@x:_JQNL(B) :
: $B0x;R$NFCD'IU$1!"(Bj=1,2,3,$B!D(B,p.
-
$BFH<+0x;R(B :
: $BJQF0!"8m:9(B
-
$B$$$/$D$+$N2>Dj(B : , , $B$N2<$G!"$3$l$i$rK~$?$9(B , $B$r5a$a$k!#(B
-
$B2sE>$NITDj@-(B: 
$B$H$J$k2sE>9TNs(BT$B$rMQ$$$k$H!"(B
$B!!!!(B
$B$H$J$j!"(BA$B$H(BF$B$NBP$OL58BAHB8:_$9$k!#0l0U$K$O7h$^$i$J$$!#(B $B2?$i$+$N4p=`$r>r7o$K3NDj$5$;$k!#(B
-
p$B
-
$B0x;R$N2r
$B0x;R<4$N2sE>(B : $BD>8r2sE>!"(B
-
$B0x;R?t$r;XDj$7$FJ,@O$r?J$a$kI,MW$,$"$k$?$a!"(B $BA0=hM}$d3NDj$7$?0x;R?t$K4p$E$/J,@OEy!"(B $B9T$-$DLa$j$D$N;n9T:x8m$,I,MW$J
- [$BNcBj(BFA] $B?)IJ$NSO9%@-$rC5$C$F$_$h$&(B
$B$N(B$B%G!<%?(B$B$rNc$K!#(B
- $B$^$:$O0x;R?t$r7h$a$h$&(B
-
$B8GM-CM(B(Eigenvalue) : $BAj4X9TNs$N8GM-CM$N?6$kIq$$$+$i0x;R?t(B($B<4?t(B)$B$r7h$a$k!#(B
- $B0x;R?t$N7hDj(B : $B2r@O
- $B8GM-CM$NBg>.!"8:>/798~$+$i0x;R?t$r7h$a$k!#(B
- $B0x;R?t$N7h$aJ}$O!"
- $BN_@Q4sM?N((B(Cumulative)
- $B8GM-CM$NCM(B(Eigenvalue, Proportion)
- $B8GM-CM4V$N%.%c%C%W(B(Difference) $BEy(B
- SAS$B%W%m%0%i%`(B : FA0711.sas
- $B=PNO7k2L(B : SAS_out0711a.txt
, Results_FA0711.pdf
Tuesday, November 17, 2020 01:07:42 AM 12
Obs X01 X02 X03 X04 X05 X06 X07 X08 X09 X10
1 7.69 7.31 7.47 7.76 7.87 7.51 7.24 7.70 7.91 7.95
2 6.59 5.56 6.21 6.04 5.81 6.64 6.11 6.53 6.44 6.64
3 4.55 4.18 4.36 4.25 4.53 4.60 3.66 4.04 3.68 4.43
4 6.78 6.11 6.30 5.98 5.56 6.37 6.29 5.43 5.32 5.28
5 6.47 6.24 6.02 5.42 5.88 6.00 5.60 4.60 5.40 5.95
6 6.96 6.81 6.91 6.48 6.23 7.09 7.27 7.13 6.86 7.36
7 6.57 5.70 5.89 5.16 5.30 6.07 5.56 4.50 4.92 5.33
8 7.32 6.95 6.02 4.98 4.88 6.82 6.40 5.53 5.61 5.33
9 6.51 6.15 5.51 4.68 4.16 5.17 4.81 4.70 4.86 3.82
10 6.86 6.05 5.85 6.14 6.75 6.71 5.39 5.42 6.03 6.59
Tuesday, November 17, 2020 01:07:42 AM 13
The FACTOR Procedure
Input Data Type Raw Data
Number of Records Read 100
Number of Records Used 100
N for Significance Tests 100
Tuesday, November 17, 2020 01:07:42 AM 14
The FACTOR Procedure
Initial Factor Method: Principal Components
Prior Communality Estimates: ONE
Eigenvalues of the Correlation Matrix: Total = 10 Average = 1
Eigenvalue Difference Proportion Cumulative
1 6.82795512 5.06608201 0.6828 0.6828
2 1.76187311 1.00742187 0.1762 0.8590
3 0.75445124 0.49207487 0.0754 0.9344
4 0.26237637 0.14082435 0.0262 0.9607
5 0.12155202 0.02358655 0.0122 0.9728
6 0.09796547 0.02586580 0.0098 0.9826
7 0.07209967 0.02801926 0.0072 0.9898
8 0.04408041 0.00832792 0.0044 0.9942
9 0.03575249 0.01385842 0.0036 0.9978
10 0.02189408 0.0022 1.0000
2 factors will be retained by the MINEIGEN criterion.
Tuesday, November 17, 2020 01:07:42 AM 15
The FACTOR Procedure
Initial Factor Method: Principal Components
Factor Pattern
Factor1 Factor2
X01 M(-15) 0.74741 -0.59244
X02 M(16-20) 0.86579 -0.31836
X03 M(21-30) 0.84491 0.22079
X04 M(31-40) 0.78216 0.47602
X05 M(41-) 0.68129 0.67325
X06 F(-15) 0.80647 -0.54140
X07 F(16-20) 0.89959 -0.33542
X08 F(21-30) 0.90901 -0.04289
X09 F(31-40) 0.90316 0.21817
X10 F(41-) 0.79262 0.35477
Variance Explained by Each Factor
Factor1 Factor2
6.8279551 1.7618731
Final Communality Estimates: Total = 8.589828
X01 X02 X03 X04 X05
0.90961791 0.85094991 0.76262367 0.83837129 0.91741340
X06 X07 X08 X09 X10
0.94352040 0.92177476 0.82814690 0.86329813 0.75411185
- $B2r
- $B8GM-CM(B(Eigenvalue) : $BAj4X9TNs$rMQ$$$?
- $BAj4X9TNs$rMQ$$$?[$B%3%a%s%H(B] $BM}2r$rFq$7$/$7$F$$$k0l$D$NM}M3$+$b$7$l$J$$(B
- $B%7%9%F%`B&$+$i$O0x;R?t$O(B2$B$@$HH=CG$5$l$?(B : $B8GM-CM$,(B1$B$h$jBg$-$$(B
- $B0x;RIi2YNL(B(Factor Pattern) :
- $B0x;RKh$NJ,;6(B(Variance explained by each factor) : $BAmJ,;6(B(10, $BJQNL?t$HEy$7$/$J$k(B)$B$N$I$l$@$1$r@bL@$7$F$$$k$+!#0x;RKh$N@bL@NL!#(B
- $B6&DL@-(B(Final Communality Estimates, $B&2(Baj^2) : $BJQ?tKh$N@bL@3d9g!#(B
- $B0x;R?t$N7hDj(B : $B2r@O
- $B8GM-CM$NJQ2=NL$+$i$9$k$H!"(B3 $B$G$bNI$5$=$&(B : 3 $B$H(B 4 $B$N4V$,6u$$$F$k(B
- $B0x;R?t$r(B 3 $B$H$7$F7W;;$7$F$_$h$&(B
- $B0x;R?t$r(B3$B$K;XDj$7$F2r@O$r?J$a$k(B
- SAS$B%W%m%0%i%`(B : FA0712.sas
- $B=PNO7k2L(B : SAS_out0712a.txt
, Results_FA0712.pdf
Tuesday, November 17, 2020 01:08:28 AM 17The FACTOR Procedure
Input Data Type Raw Data
Number of Records Read 100
Number of Records Used 100
N for Significance Tests 100
Tuesday, November 17, 2020 01:08:28 AM 18
The FACTOR Procedure
Initial Factor Method: Principal Components
Prior Communality Estimates: ONE
Eigenvalues of the Correlation Matrix: Total = 10 Average = 1
Eigenvalue Difference Proportion Cumulative
1 6.82795512 5.06608201 0.6828 0.6828
2 1.76187311 1.00742187 0.1762 0.8590
3 0.75445124 0.49207487 0.0754 0.9344
4 0.26237637 0.14082435 0.0262 0.9607
5 0.12155202 0.02358655 0.0122 0.9728
6 0.09796547 0.02586580 0.0098 0.9826
7 0.07209967 0.02801926 0.0072 0.9898
8 0.04408041 0.00832792 0.0044 0.9942
9 0.03575249 0.01385842 0.0036 0.9978
10 0.02189408 0.0022 1.0000
3 factors will be retained by the NFACTOR criterion.
Tuesday, November 17, 2020 01:08:28 AM 19
The FACTOR Procedure
Initial Factor Method: Principal Components
Factor Pattern
Factor1 Factor2 Factor3
X01 M(-15) 0.74741 -0.59244 0.16808
X02 M(16-20) 0.86579 -0.31836 0.29190
X03 M(21-30) 0.84491 0.22079 0.38417
X04 M(31-40) 0.78216 0.47602 0.32604
X05 M(41-) 0.68129 0.67325 0.11067
X06 F(-15) 0.80647 -0.54140 -0.07270
X07 F(16-20) 0.89959 -0.33542 -0.14888
X08 F(21-30) 0.90901 -0.04289 -0.25110
X09 F(31-40) 0.90316 0.21817 -0.27989
X10 F(41-) 0.79262 0.35477 -0.45389
Variance Explained by Each Factor
Factor1 Factor2 Factor3
6.8279551 1.7618731 0.7544512
Final Communality Estimates: Total = 9.344279
X01 X02 X03 X04 X05
0.93786990 0.93615660 0.91021020 0.94467297 0.92966229
X06 X07 X08 X09 X10
0.94880526 0.94393897 0.89119742 0.94163724 0.96012863
Tuesday, November 17, 2020 01:08:28 AM 20
The FACTOR Procedure
Initial Factor Method: Principal Components
Scoring Coefficients Estimated by Regression
Squared Multiple Correlations of the Variables with Each Factor
Factor1 Factor2 Factor3
1.0000000 1.0000000 1.0000000
Standardized Scoring Coefficients
Factor1 Factor2 Factor3
X01 M(-15) 0.10946 -0.33626 0.22279
X02 M(16-20) 0.12680 -0.18069 0.38691
X03 M(21-30) 0.12374 0.12531 0.50920
X04 M(31-40) 0.11455 0.27018 0.43215
X05 M(41-) 0.09978 0.38212 0.14670
X06 F(-15) 0.11811 -0.30729 -0.09636
X07 F(16-20) 0.13175 -0.19038 -0.19733
X08 F(21-30) 0.13313 -0.02434 -0.33282
X09 F(31-40) 0.13227 0.12383 -0.37099
X10 F(41-) 0.11609 0.20136 -0.60162
Tuesday, November 17, 2020 01:08:28 AM 21
Plot of Factor1*Factor2. Legend: A = 1 obs, B = 2 obs, etc.
Factor1 | |
| |
3 + |
| |
| |
| | A
2 + |A
| A A | A
| A|A A
| A A | A A
1 + A A A A A A
| A A C A |AB A
| A AA A AA | A A A
| A A A BA A AA A A A
0 +-------------------A------------------A-A-----B--A-AAA---A-----A--A--
| A A A | A
| A A| A A
| A A A A A A A | A B A
-1 + A A | A AB A A
| A | A A
| | AA A
| A |
-2 + A A | A A
| |
| | A
| |
-3 + |
| |
--+------------+------------+------------+------------+------------+--
-3 -2 -1 0 1 2
Factor2
Tuesday, November 17, 2020 01:08:28 AM 22
Plot of Factor2*Factor3. Legend: A = 1 obs, B = 2 obs, etc.
Factor2 | |
| |
2 + | A
| A A | A
| A | A
| A | AA A
| A | A A
1 + A A AA A| A
| A A B A | A
| A AA A A A| A A
| A A A | A A AA A
| AA AAA A | B A A
0 +----------A----B-A-----+-AB------------------------------------------
| B | BA
| A A A| A A A A
| A AA| A AAA
| A | A
-1 + A A A AA
| A A A A
| A AAA
| A A A| A
| A |
-2 + AA |
| |
| |
| |
| | A
-3 + |
| |
--+----------+----------+----------+----------+----------+----------+-
-2 -1 0 1 2 3 4
Factor3
- $B2r.$+$i!#(B
- $B8GM-CM(B(Eigenvalue)
- $B0x;RKh$NJ,;6(B(Variance explained by each factor) : $B0x;RKh$N@bL@NL!#(B
- $B6&DL@-(B(Final Communality Estimates, $B&2(Baj^2) : $BJQ?tKh$N@bL@3d9g!#(B
- $B4sM?N((B(Proportion) : $B3F0x;R$N@bL@NO$NBg$-$5(B
- $BN_@Q4sM?N((B(Cumulative)
- 3$B0x;R$^$H$a$F$N@bL@NO$NBg$-$5(B : 93.4%
- $B0x;RIi2YNL(B($BI8=`2=%9%3%"78?t(B, Standardized Scoring Coefficients) :
: $B%i%$%s%^!<%+!<$NMxMQ$,8z2LE*(B
- $BBh(B1$B0x;R(B : $BA4BNE*$JSO9%(B
- $BBh(B2$B0x;R(B : $BG/Np8z2L(B (+ $BG/GZ!"(B- $B $BBh(B3$B0x;R(B : $B@-JL8z2L(B (+ $BCK@-!"(B- $B=w@-(B)
- $B3F8DBN$N0x;RF@E@(B()$B$N;6I[?^(B :
- $B3F8DBN$N6qBNE*$J0LCV$rGD0.(B
- $BBh(B2$B0x;R$HBh(B3$B0x;R$N4X78$,LLGr$=$&(B
- $B2sE>$5$;$F$_$h$&(B : $B$?$@$7!"2sE>$,I,?\$G$O$J$$(B
- $B2sE>$NITDj@-$+$i!#(B
- $B2sE>$5$;$?J}$,2r
- $BBeI=E*$JD>8r2sE>$N(BVarimax$B$rE,MQ$7$F$_$k(B
- SAS$B%W%m%0%i%`(B : FA0713.sas
- $B=PNO7k2L(B : SAS_out0713a.txt
, Results_FA0713.pdf
Tuesday, November 17, 2020 01:09:11 AM 24The FACTOR Procedure
Input Data Type Raw Data
Number of Records Read 100
Number of Records Used 100
N for Significance Tests 100
Tuesday, November 17, 2020 01:09:11 AM 25
The FACTOR Procedure
Initial Factor Method: Principal Components
Prior Communality Estimates: ONE
Eigenvalues of the Correlation Matrix: Total = 10 Average = 1
Eigenvalue Difference Proportion Cumulative
1 6.82795512 5.06608201 0.6828 0.6828
2 1.76187311 1.00742187 0.1762 0.8590
3 0.75445124 0.49207487 0.0754 0.9344
4 0.26237637 0.14082435 0.0262 0.9607
5 0.12155202 0.02358655 0.0122 0.9728
6 0.09796547 0.02586580 0.0098 0.9826
7 0.07209967 0.02801926 0.0072 0.9898
8 0.04408041 0.00832792 0.0044 0.9942
9 0.03575249 0.01385842 0.0036 0.9978
10 0.02189408 0.0022 1.0000
3 factors will be retained by the NFACTOR criterion.
Tuesday, November 17, 2020 01:09:11 AM 26
The FACTOR Procedure
Initial Factor Method: Principal Components
Factor Pattern
Factor1 Factor2 Factor3
X01 M(-15) 0.74741 -0.59244 0.16808
X02 M(16-20) 0.86579 -0.31836 0.29190
X03 M(21-30) 0.84491 0.22079 0.38417
X04 M(31-40) 0.78216 0.47602 0.32604
X05 M(41-) 0.68129 0.67325 0.11067
X06 F(-15) 0.80647 -0.54140 -0.07270
X07 F(16-20) 0.89959 -0.33542 -0.14888
X08 F(21-30) 0.90901 -0.04289 -0.25110
X09 F(31-40) 0.90316 0.21817 -0.27989
X10 F(41-) 0.79262 0.35477 -0.45389
Variance Explained by Each Factor
Factor1 Factor2 Factor3
6.8279551 1.7618731 0.7544512
Final Communality Estimates: Total = 9.344279
X01 X02 X03 X04 X05
0.93786990 0.93615660 0.91021020 0.94467297 0.92966229
X06 X07 X08 X09 X10
0.94880526 0.94393897 0.89119742 0.94163724 0.96012863
Tuesday, November 17, 2020 01:09:11 AM 27
The FACTOR Procedure
Rotation Method: Varimax
Orthogonal Transformation Matrix
1 2 3
1 0.65777 0.53529 0.52990
2 -0.73396 0.61357 0.29126
3 0.16922 0.58051 -0.79647
Rotated Factor Pattern
Factor1 Factor2 Factor3
X01 M(-15) 0.95490 0.13415 0.08963
X02 M(16-20) 0.85255 0.43757 0.13357
X03 M(21-30) 0.45872 0.81076 0.20605
X04 M(31-40) 0.22027 0.90003 0.29343
X05 M(41-) -0.02727 0.84202 0.46896
X06 F(-15) 0.91555 0.05731 0.32756
X07 F(16-20) 0.81272 0.18932 0.49758
X08 F(21-30) 0.58692 0.31451 0.66919
X09 F(31-40) 0.38658 0.45484 0.76506
X10 F(41-) 0.18417 0.37847 0.88485
Variance Explained by Each Factor
Factor1 Factor2 Factor3
3.9249494 2.8740019 2.5453282
Tuesday, November 17, 2020 01:09:11 AM 28
The FACTOR Procedure
Rotation Method: Varimax
Final Communality Estimates: Total = 9.344279
X01 X02 X03 X04 X05
0.93786990 0.93615660 0.91021020 0.94467297 0.92966229
X06 X07 X08 X09 X10
0.94880526 0.94393897 0.89119742 0.94163724 0.96012863
Tuesday, November 17, 2020 01:09:11 AM 29
The FACTOR Procedure
Rotation Method: Varimax
Scoring Coefficients Estimated by Regression
Squared Multiple Correlations of the Variables with Each Factor
Factor1 Factor2 Factor3
1.0000000 1.0000000 1.0000000
Standardized Scoring Coefficients
Factor1 Factor2 Factor3
X01 M(-15) 0.35650 -0.01839 -0.21738
X02 M(16-20) 0.28150 0.18161 -0.29360
X03 M(21-30) 0.07559 0.43873 -0.30350
X04 M(31-40) -0.04982 0.47796 -0.20481
X05 M(41-) -0.19000 0.37303 0.04733
X06 F(-15) 0.28692 -0.18126 0.04983
X07 F(16-20) 0.19300 -0.16084 0.17154
X08 F(21-30) 0.04912 -0.13688 0.32854
X09 F(31-40) -0.06666 -0.06858 0.40164
X10 F(41-) -0.17324 -0.16356 0.59933
Tuesday, November 17, 2020 01:09:11 AM 30
Obs X01 X02 X03 X04 X05 X06 X07 X08
1 7.69 7.31 7.47 7.76 7.87 7.51 7.24 7.70
2 6.59 5.56 6.21 6.04 5.81 6.64 6.11 6.53
3 4.55 4.18 4.36 4.25 4.53 4.60 3.66 4.04
4 6.78 6.11 6.30 5.98 5.56 6.37 6.29 5.43
5 6.47 6.24 6.02 5.42 5.88 6.00 5.60 4.60
6 6.96 6.81 6.91 6.48 6.23 7.09 7.27 7.13
7 6.57 5.70 5.89 5.16 5.30 6.07 5.56 4.50
8 7.32 6.95 6.02 4.98 4.88 6.82 6.40 5.53
9 6.51 6.15 5.51 4.68 4.16 5.17 4.81 4.70
10 6.86 6.05 5.85 6.14 6.75 6.71 5.39 5.42
11 7.04 6.03 6.53 6.02 6.68 6.78 5.91 6.26
12 6.59 6.30 6.29 5.94 6.10 5.93 5.52 5.35
13 5.93 4.76 5.09 5.51 5.79 5.49 4.97 4.69
14 7.00 6.31 6.82 6.26 5.26 6.69 6.27 5.94
15 6.63 5.47 5.54 4.88 4.70 5.89 4.64 4.43
16 6.56 6.57 5.74 4.76 4.39 6.56 6.29 5.61
Obs X09 X10 Factor1 Factor2 Factor3
1 7.91 7.95 0.66956 1.82121 1.58069
2 6.44 6.64 0.16626 -0.19916 1.19252
3 3.68 4.43 -1.03468 -1.43973 -0.47173
4 5.32 5.28 0.63900 0.22553 -0.50004
5 5.40 5.95 0.18242 0.09152 -0.20811
6 6.86 7.36 0.74034 0.36710 1.34854
7 4.92 5.33 0.32215 -0.32438 -0.54816
8 5.61 5.33 1.29334 -0.70969 -0.33933
9 4.86 3.82 0.58581 -0.75180 -1.38820
10 6.03 6.59 0.02089 0.39898 0.55070
11 5.76 5.95 0.40396 0.58950 0.17643
12 5.45 5.85 0.19873 0.54822 -0.27773
13 5.30 5.61 -0.59976 -0.44330 0.31921
14 5.78 5.26 0.91645 0.42072 -0.53512
15 4.00 3.98 0.46299 -0.53468 -1.57421
16 5.22 4.72 1.10983 -1.07931 -0.45219
$B"cCfN,"d(B
Tuesday, November 17, 2020 01:09:12 AM 37
Plot of Factor1*Factor2. Legend: A = 1 obs, B = 2 obs, etc.
2 + | A
| A |
| |
| A A A |
| A A | A A
| A |A A
| A A | A A
1 + | A
| A B | B A
| A A AA A A A A
Factor1 | A A A A A A
| A A | A A A A
| A | A A
| A |A A A
0 +--------------------------------A-+-A-A------------------------------
| A A A | AA
| A AA | A A A
| A A| A A
| AA |
| |
| A A|A BA A
-1 + A AA A | A
| A A | A
| A A A | A A
| AA A | A A
| | A
| |
| A A |
-2 + A| A
--+----------+----------+----------+----------+----------+----------+-
-3 -2 -1 0 1 2 3
Factor2
Tuesday, November 17, 2020 01:09:12 AM 38
Plot of Factor2*Factor3. Legend: A = 1 obs, B = 2 obs, etc.
Factor2 | |
| |
3 + |
| A |
| A |
| |
2 + A |
| | A A
| A A | A A
| A A | A A
1 + | AAA A A A A
| | A A A
| A A A A A AA |AAA A
| B A AA A| A AA A A A
0 +-------------------------------------A-----A-+--AA---AAAA------------
| AA |AB A AB A
| A A AA| AAA A A A
| A A A A | A A
-1 + A A| A A
| A A A A | A A A
| A A | A AA
| A A A |
-2 + A |
| |
| |
| |
-3 + |
| |
--+----------+----------+----------+----------+----------+----------+-
-4 -3 -2 -1 0 1 2
Factor3
Tuesday, November 17, 2020 01:09:12 AM 39
Plot of Factor3*Factor1. Legend: A = 1 obs, B = 2 obs, etc.
Factor3 | |
| |
2 + |
| A | A
| A A |A AA
| A | A AA
1 + A A A A | AA
| A AAA AA CB | A A
| A A A AA A A
| A A A A A A A | AB AA B A AA
0 +---------------------A------------------+--A---------------B---------
| A | AA A AA A A
| A A A A| A A A A A A
| A A | A AAA A
-1 + A A A| AA
| A A |
| A A |A A A A
| |
-2 + |
| A |
| | A
| A |
-3 + |
| |
| A |
| |
-4 + |
| |
--+------------+------------+------------+------------+------------+--
-3 -2 -1 0 1 2
Factor1
- $B2r.$+$i!#(B
- ($B2sE>9TNs(B, Orthogonal Transformation Matrix)
- $B0x;RKh$NJ,;6(B(Variance explained by each factor) : $B0x;RKh$N@bL@NL!#(B
- $B6&DL@-(B(Final Communality Estimates, $B&2(Baj^2) : $BJQ?tKh$N@bL@3d9g!#(B
- $B4sM?N((B(Proportion) : $B3F0x;R$N@bL@NO$NBg$-$5(B
- $BN_@Q4sM?N((B(Cumulative) :
- 3$B0x;R$^$H$a$F$N@bL@NO$NBg$-$5(B : 93.4%
- $B0x;RIi2YNL(B($BI8=`2=%9%3%"78?t(B, Standardized Scoring Coefficients) :
- $BBh(B1$B0x;R(B : $B $BBh(B2$B0x;R(B : $B@.?MCK@-$NSO9%(B (+ $B@.G/CK;R(B)
- $BBh(B3$B0x;R(B : $B@.?M=w@-$NSO9%(B (+ $B@.G/=w;R(B)
- $B3F8DBN$N0x;RF@E@(B()$B$N;6I[?^(B :
- $B3F8DBN$N6qBNE*$J0LCV$rGD0.(B
- $B3F0x;R4V$N4X78$,LLGr$$!#(B
- $B2sE>A0$H2sE>8e$G$I$N$h$&$K2r
- $BBeI=E*$J2sE>K!(B :
- $B%P%j%^%C%/%9K!(B(rotate=varimax) : $BD>8r2sE>(B : $B0x;R<44V$OD>8r(B($B0x;R<4F1;N$OFHN)(B($BL5Aj4X(B))
- $B%W%m%^%C%/%9K!(B(rotate=promax) : $B(B : $B0x;R<44V$KAj4X@-(B
- $B
- p$Be5-(B3$B0x;R$G2r $B6aK5$N0x;R?t(B(2$B$H$+(B4$B$H$+(B)$B$G;n$7$F$_$k$N$b0l0F$G$"$k!#(B
- $B2sE>$5$;$J$$$H$-$H!"2sE>$5$;$?$H$-$G$I$A$i$,2r
- $B0x;R?t$r;XDj$7$FJ,@O$r?J$a$kI,MW$,$"$k$?$a!"(B $BA0=hM}$d3NDj$7$?0x;R?t$K4p$E$/J,@OEy!"(B $B9T$-$DLa$j$D$N;n9T:x8m$,I,MW$J $B%G!<%?$N%P%C%/%0%i%&%s%I$rGD0.$7$F$$$k$H!"0x;R$N2r
- $B0x;R?t$N7hDj4p=`(B
- $BL@3N$K7h$^$C$F$$$k$o$1$G$O$J$$(B : $B $B7k2L$N2re!"B?>/A}8:$5$;$k$3$H$b$"$k(B : $B;n9T:x8m(B
- $BN_@Q4sM?N($,$"$kDxEY(B($BNc$($P(B80%$B0J>e(B)$B0J>eBg$-$/$J$k$3$H(B
- $B8GM-CM$N%.%c%C%W$,$"$kDxEY0J>eBg$-$$$3$H(B
- $B8GM-CM$,(B 1$B0J>e(B
- ...
- $B
- $BL\E*(B: $B$$$/$D$+(B(p$B8D(B)$B$NJQNL$N>pJs$r!"B;<:$r$G$-$k$@$1>/$J$/$7$F!"(B $B>/?tJQNL(B(m$B8D!"(Bm$B!c(Bp)$B$NAm9gE*;XI8(B($B
- $B9M$(J}(B
- $B $B0x;RJ,@O(B : $B%b%G%k$NF3F~!"2sE>@-!"0l0U@-$K5?Ld(B($BFC$K(B)
- $BBP>]%G!<%?(B
- $B%5%s%W%k%5%$%:$N$"$kDxEYBg$-$$%G!<%?$,BP>]$H$J$k(B
- $BJQNL?t$b$"$kDxEYBg$-$$%G!<%?$,BP>]$H$J$k(B
- $BEvA3$J$,$i%5%s%W%k%5%$%:$NJ}$,JQNL?t$h$j$bBg$-$$$3$H(B : $BB?JQNL2r@OA4HL(B
- $BBP>]%G!<%?$r=OCN$7$F$$$kJ}$,2r $B0x;R$NFCD'IU$1$O%G!<%?$N%P%C%/%0%i%&%s%I$K?<$/4X78(B
- $B7P83$r@Q$`$H$h$jG $B@x:_E*$J9=B$$,2>Dj$G$-$k$+(B? $B%b%G%k$,E,MQ2DG=$JLdBj$+6cL#$9$kI,MW@-!#(B
- $B<4?t!"
[$B%N%&%O%&(B] $B%i%$%s%^!<%+!<$G@dBPCM$NBg$-$$JQNL$K%^!<%/$rIU$1$k(B
- $B$$$m$$$m$J%G!<%?$G7P83$r@Q$s$G$_$k!#(B
- $B$I$C$A$r;H$&(B? : $B$d$C$F$_$k!#2r ...
- $B%G!<%?$K$h$C$F$O2r
- 12$B7n(B01$BF|(B($B2P(B): $B%l%]!<%H:n@.$K=<$F$F$/$@$5$$!#(B
- $B9V5A$O9T$o$J$$$3$H$K$7$^$9!#(B
- $B9V5AFbMFA4HL$K4X$7$F!"$4 $BEvF|!"K\Mh$N9V5A3+:E;~4VBS(B(16:20-17:50)$B$K$O(B2311$B65<<$KBT5!$7$F$*$/$3$H$K$7$^$9!#(B
- $BB>$NF|Dx$G$bBP1~$7$^$9$N$G!"$=$N:]$O8&5f<<$r$*K,$M$/$@$5$$!#(B11$B9f4[(B 5$B3,(B 516$B< $B3'$5$s$,$*;}$A$N%G!<%?$H$=$N2r@O$N>R2p(B
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- Q4$B$r7^$($k$K$"$?$C$F(B
$B!!0JA0$+$i$*CN$i$;$7$F$$$kDL$j!"(BQ4$B$G$OE}7W%=%U%H%&%'%"!V(B
SAS OnDemand for Academics
$B!W$r;H$C$?E}7W2r@O$N>N$NE}7W%=%U%H%&%'%"(B)$B$N%5!<%P!<$K%$%s%?!<%M%C%H$rDL$8$F@\B3$7!"(B
$B$4<+?H$N%Q%=%3%s$rCSAS University Edition
$B$=$N:]$K!V$4<+?H$N%Q%=%3%s!W$K%=%U%H$r%$%s%9%H!<%k$9$kI,MW$,$"$j$^$9!#(B
$B$^$?!"Jd=u5-21AuCV(B(HDD$BEy(B)$B$K$"$kDxEY$N6u$-NN0h$,$"$kI,MW$b$"$j$^$9!#(B
--
$B!!$b$7$*;}$A$N%Q%=%3%s$r65<<$K;}$C$F$/$k$3$H$,$G$-$J$$J}$,$*$i$l$k$h$&$J>l9g$O(B
$B$I$&$7$^$7$g$&$M(B? $B8D?ME*$K$4AjCL2<$5$$!#(B
--
$B!!$=$l$H!"]$K$9$k$H!"(B
$BE}7W]$H$7$?J,@O$r3F<+$G9T$J$C$F$$$?$@$3$&$H9M$($F$$$^$9$N$G!"(B
$B!V3F<+$G%G!<%?$r8+$D$1$F$/$k$3$H!W$b$*4j$$$7$?$$$H;W$C$F$$$^$9!#(B
$B!!0J>e$N$h$&$J>u67$G$O$"$j$^$9$,!"(B
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$B!!?M?t$rGD0.$7$?$$$H;W$$$^$9$N$G!"(B
$B$5$l$kJ}$O!"!VE}7W%b%G%k2r@OFCO@-6!W$N%3!<%9Fb$K@_CV$7$?(B
$BD0
- Q3$B$r=*$($k$K$"$?$C$F(B
$B!!(B
$B=i$a$F$N%j%b!<%H9V5A$H$$$&$3$H$G!"Kh2sGvI9$rF'$`;W$$$G$7$?!#(B
$B2?$H$+$3$3$^$GC)$jCe$1$?$H$$$&5$;}$A$G$9$,!"$^$:$O$*IU$-9g$$2<$5$j!"(B
$B$I$&$b$"$j$,$H$&$4$6$$$^$7$?!#(B
$B!!$3$N9V5A$rDL$7$F!"!V%G!<%?$H$N@\$7J}!W$d!VE}7W$N9M$(J}!W$,B?>/$J$j$H$bM}2r$G$-$?$G$"$m$&$+(B?
$BBgNL$N?tCM72$+$iFb:_$9$k9=B$$r8+$D$1$k$3$H$,!V2r@O!W$G$"$j!VE}7W$NLLGrL#!W$G$b$"$k$H;W$&!#(B
$B$=$N$?$a$K$O!"M}O@$dL\E*$rCN$C$F$$$kI,MW$,$"$k$N$OL^O@$@$,!"BP>]$H$9$k%G!<%?$NGX7J$rCN$C$F$*$/$3$H$d!"(B
$BE}7W%=%U%H$r(B"$BF;6q(B"$B$H$7$F;H$$$3$J$9I,MW$b$"$m$&!#(B
$B!!B?JQNL2r@O$H8F$P$l$kE}7W/?($l$?$D$b$j$G$"$k!#(B
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$B!!2C$($FE}7W3X$+$i8+$kBg3XF~;n$K$^$D$o$kOCBj$b?%$j9~$s$G$_$?!#(B
$B!!:#8e!"?7J9$d;(;o$H8@$C$?@83h$G$OL^O@$N$3$H!"8&5f$d$$$m$$$m$J>lLL$G!"
$B!!$J$*!":#8e!"$b$7E}7W$K4X$7$F2?$+5?Ld$K=P2q$$!";d$KAjCL$7$F$_$?$$$H;W$C$?:]$O!"1sN8L5$/$4O"Mm2<$5$$!#(B
$B!!3'$5$s$N4|BT$K$I$3$^$G1~$($i$l$?$+?45vL5$$ItJ,$b$"$j$^$9$,!"(B7$B2s(B(+1$B2s(B)$B$N9V5A!"$*IU$-9g$$$/$@$5$j!"$I$&$b$"$j$,$H$&$4$6$$$^$7$?!#$*Hh$l$5$^$G$7$?!#(B
$B!!!!(B($B@)Ls>r7o(B : 
$B$N2<$G(B)
$B!#(B
$B!"6&J,;6$r(B 
$B$H$9$k!#(B
$B$N2<$G(B)