library(plspm)
data(satisfaction)
IMAG <- c(0,0,0,0,0,0)
EXPE <- c(1,0,0,0,0,0)
QUAL <- c(0,1,0,0,0,0)
VAL <- c(0,1,1,0,0,0)
SAT <- c(1,1,1,1,0,0)
LOY <- c(1,0,0,0,1,0)
sat.mat <-rbind(IMAG, EXPE, QUAL, VAL, SAT, LOY)
#上面定义的矩阵与内部关系方程中的矩阵相同
#下面语句把显变量分配到与其有关的隐变量确定测量模型
sat.sets <-list(1:5,6:10,11:15,16:19,20:23,24:27)
sat.mod <-rep("A",6)
#上面"A"说明6组显变量都是反映型的("B"意味着显变量是影响型的)
res=plspm(satisfaction,sat.mat,sat.sets,sat.mod,scaled=F)
summary(res)
innerplot(res) #绘制路径图-含系数
PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)
----------------------------------------------------------
MODEL SPECIFICATION模型设定
1 Number of Cases 250
2 Latent Variables 6
3 Manifest Variables 27
4 Scale of Data Raw Data
5 Non-Metric PLS FALSE
6 Weighting Scheme centroid
7 Tolerance Crit 1e-06
8 MaxNum Iters 100
9 Convergence Iters 4
10 Bootstrapping FALSE
11 Bootstrap samples NULL
----------------------------------------------------------
BLOCKS DEFINITION 构念设定
Block Type Size Mode(反映模型)
1 IMAG Exogenous 5 A
2 EXPE Endogenous 5 A
3 QUAL Endogenous 5 A
4 VAL Endogenous 4 A
5 SAT Endogenous 4 A
6 LOY Endogenous 4 A
----------------------------------------------------------
BLOCKS UNIDIMENSIONALITY 信度
Mode MVs C.alpha DG.rho eig.1st eig.2nd
IMAG A 5 0.830 0.882 3.02 0.778
EXPE A 5 0.847 0.891 3.10 0.611
QUAL A 5 0.871 0.907 3.31 0.568
VAL A 4 0.836 0.890 2.68 0.601
SAT A 4 0.894 0.927 3.04 0.422
LOY A 4 0.819 0.881 2.60 0.573
----------------------------------------------------------
OUTER MODEL
weight loading communality(公因式分叉) redundancy(冗余度)
IMAG
1imag1 0.0982 0.709 0.503 0.000
1imag2 0.1575 0.877 0.770 0.000
1imag3 0.1567 0.842 0.709 0.000
1imag4 0.0766 0.569 0.324 0.000
1imag5 0.1843 0.778 0.606 0.000
EXPE
2expe1 0.1062 0.766 0.586 0.197
2expe2 0.1407 0.837 0.701 0.235
2expe3 0.1188 0.760 0.577 0.194
2expe4 0.0995 0.718 0.516 0.173
2expe5 0.1384 0.837 0.701 0.235
QUAL
3qual1 0.1066 0.781 0.611 0.440
3qual2 0.1346 0.882 0.777 0.559
3qual3 0.1171 0.794 0.631 0.454
3qual4 0.0956 0.789 0.622 0.448
3qual5 0.1157 0.807 0.652 0.469
VAL
4val1 0.1750 0.865 0.748 0.441
4val2 0.1177 0.796 0.634 0.374
4val3 0.1208 0.750 0.563 0.332
4val4 0.1665 0.844 0.713 0.421
SAT
5sat1 0.1664 0.920 0.846 0.598
5sat2 0.1627 0.916 0.839 0.594
5sat3 0.1211 0.826 0.682 0.482
5sat4 0.1321 0.818 0.668 0.473
LOY
6loy1 0.1586 0.907 0.822 0.419
6loy2 0.0817 0.671 0.450 0.230
6loy3 0.1617 0.905 0.819 0.418
6loy4 0.0807 0.682 0.465 0.237
----------------------------------------------------------
CROSSLOADINGS 交叉载荷
IMAG EXPE QUAL VAL SAT LOY
IMAG
1imag1 0.709 0.314 0.313 0.425 0.394 0.397
1imag2 0.877 0.480 0.534 0.608 0.597 0.544
1imag3 0.842 0.477 0.515 0.663 0.646 0.555
1imag4 0.569 0.270 0.313 0.406 0.346 0.347
1imag5 0.778 0.532 0.589 0.539 0.556 0.474
EXPE
2expe1 0.402 0.766 0.631 0.500 0.463 0.363
2expe2 0.511 0.837 0.749 0.591 0.547 0.420
2expe3 0.406 0.760 0.627 0.479 0.415 0.323
2expe4 0.492 0.718 0.621 0.561 0.509 0.446
2expe5 0.476 0.837 0.695 0.556 0.507 0.386
QUAL
3qual1 0.461 0.685 0.781 0.598 0.554 0.504
3qual2 0.552 0.746 0.882 0.687 0.629 0.528
3qual3 0.445 0.666 0.794 0.580 0.501 0.379
3qual4 0.632 0.626 0.789 0.635 0.592 0.604
3qual5 0.524 0.708 0.807 0.614 0.571 0.508
VAL
4val1 0.628 0.663 0.713 0.865 0.750 0.591
4val2 0.510 0.473 0.554 0.796 0.676 0.574
4val3 0.485 0.432 0.514 0.750 0.540 0.484
4val4 0.637 0.591 0.669 0.844 0.696 0.607
SAT
5sat1 0.648 0.585 0.654 0.805 0.920 0.672
5sat2 0.642 0.623 0.711 0.795 0.916 0.602
5sat3 0.523 0.453 0.543 0.622 0.826 0.493
5sat4 0.585 0.461 0.498 0.608 0.818 0.604
LOY
6loy1 0.570 0.457 0.555 0.652 0.664 0.907
6loy2 0.410 0.306 0.378 0.403 0.399 0.671
6loy3 0.572 0.476 0.592 0.647 0.657 0.905
6loy4 0.374 0.223 0.340 0.433 0.344 0.682
----------------------------------------------------------
INNER MODEL (内部模型)
$EXPE
Estimate Std. Error t value Pr(>|t|)
Intercept 3.79e-17 0.0518 7.32e-16 1.00e+00
IMAG 5.79e-01 0.0518 1.12e+01 8.96e-24
$QUAL
Estimate Std. Error t value Pr(>|t|)
Intercept 6.28e-17 0.0336 1.87e-15 1.00e+00
EXPE 8.48e-01 0.0336 2.52e+01 1.92e-70
$VAL
Estimate Std. Error t value Pr(>|t|)
Intercept 9.08e-17 0.0407 2.23e-15 1.00e+00
EXPE 1.05e-01 0.0769 1.37e+00 1.72e-01
QUAL 6.77e-01 0.0769 8.79e+00 2.52e-16
$SAT
Estimate Std. Error t value Pr(>|t|)
Intercept -3.60e-18 0.0346 -1.04e-16 1.00e+00
IMAG 2.01e-01 0.0499 4.02e+00 7.74e-05
EXPE -2.75e-03 0.0657 -4.19e-02 9.67e-01
QUAL 1.22e-01 0.0752 1.62e+00 1.06e-01
VAL 5.89e-01 0.0600 9.82e+00 2.10e-19
$LOY
Estimate Std. Error t value Pr(>|t|)
Intercept 3.70e-17 0.0445 8.31e-16 1.00e+00
IMAG 2.75e-01 0.0617 4.46e+00 1.25e-05
SAT 4.95e-01 0.0617 8.03e+00 4.01e-14
----------------------------------------------------------
CORRELATIONS BETWEEN LVs 因子相关
IMAG EXPE QUAL VAL SAT LOY
IMAG 1.000 0.579 0.634 0.705 0.692 0.618
EXPE 0.579 1.000 0.848 0.679 0.618 0.485
QUAL 0.634 0.848 1.000 0.766 0.699 0.609
VAL 0.705 0.679 0.766 1.000 0.823 0.694
SAT 0.692 0.618 0.699 0.823 1.000 0.686
LOY 0.618 0.485 0.609 0.694 0.686 1.000
----------------------------------------------------------
SUMMARY INNER MODEL 内部模型摘要
Type R2 Block_Communality Mean_Redundancy AVE
IMAG Exogenous 0.000 0.582 0.000 0.582
EXPE Endogenous 0.335 0.616 0.207 0.616
QUAL Endogenous 0.720 0.659 0.474 0.659
VAL Endogenous 0.590 0.664 0.392 0.664
SAT Endogenous 0.707 0.759 0.537 0.759
LOY Endogenous 0.510 0.639 0.326 0.639
----------------------------------------------------------
GOODNESS-OF-FIT 0.25中- 0.36较好
[1] 0.6097
----------------------------------------------------------
TOTAL EFFECTS
relationships direct indirect total
1 IMAG -> EXPE 0.57896 0.000 0.579
2 IMAG -> QUAL 0.00000 0.491 0.491
3 IMAG -> VAL 0.00000 0.393 0.393
4 IMAG -> SAT 0.20072 0.290 0.491
5 IMAG -> LOY 0.27515 0.243 0.518
6 EXPE -> QUAL 0.84834 0.000 0.848
7 EXPE -> VAL 0.10548 0.574 0.680
8 EXPE -> SAT -0.00275 0.504 0.501
9 EXPE -> LOY 0.00000 0.248 0.248
10 QUAL -> VAL 0.67666 0.000 0.677
11 QUAL -> SAT 0.12214 0.399 0.521
12 QUAL -> LOY 0.00000 0.258 0.258
13 VAL -> SAT 0.58933 0.000 0.589
14 VAL -> LOY 0.00000 0.292 0.292
15 SAT -> LOY 0.49548 0.000 0.495
