Tải dữ liệu
setwd("/Users/thuphan/Desktop/R-STUDIO")
library(seminr)
library(readxl)
dulieu <- read_excel("dulieuold.xlsx")
dulieu <-na.omit(dulieu)
head(dulieu)
## # A tibble: 6 × 37
## OIBB1 OIBB2 OIBB3 OIBB4 OIBB5 SM1 SM2 SM3 SM4 SM5 HM1 HM2 HM3
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## 2 1 1 1 1 1 1 2 1 1 1 1 1 1
## 3 1 1 1 1 1 1 3 1 1 1 2 2 2
## 4 2 2 2 2 2 1 1 1 1 1 1 1 1
## 5 1 1 1 1 1 1 1 1 1 1 3 3 1
## 6 3 2 3 3 3 1 1 1 2 2 1 1 2
## # ℹ 24 more variables: HM4 <dbl>, HM5 <dbl>, IST1 <dbl>, IST2 <dbl>,
## # IST4 <dbl>, IST5 <dbl>, IST6 <dbl>, IST7 <dbl>, IST8 <dbl>, IST9 <dbl>,
## # IST10 <dbl>, IST11 <dbl>, IST12 <dbl>, SI1 <dbl>, SI2 <dbl>, SI3 <dbl>,
## # SI4 <dbl>, SI5 <dbl>, SI6 <dbl>, SI9 <dbl>, SI12 <dbl>, SI13 <dbl>,
## # SI14 <dbl>, SI15 <dbl>
1. Thiết lập thang đo
thangdo <- constructs(
composite("X1", multi_items("OIBB", 1:5), weights = mode_A),
composite("X2", multi_items("SM", 1:5), weights = mode_A),
composite("X3", multi_items("HM", 1:5), weights = mode_A),
composite("X4", multi_items("IST", c(1:2,4:12)), weights = mode_A),
composite("X5", multi_items("SI", c( 1:6,9,12:15)), weights = mode_A),
interaction_term(iv = "X2", moderator = "X5", weights = mode_A, method = two_stage),
interaction_term(iv = "X3", moderator = "X5", weights = mode_A, method = two_stage) # nhớ xoá "," cuối này
)
2. Thiết lập mối quan hệ
moiquanhe <-relationships(
paths(from = c("X2", "X3", "X4","X5","X2*X5","X3*X5"), to =c("X1")),
paths(from = c("X2", "X3"), to =c("X4"))
)
3. Chạy mô hình
3.1 Chạy CFA
cfa <- estimate_cfa(
data = dulieu,
measurement_model = as.reflective(thangdo) #(thang đo phải là reflective khong composite)
)
#cfa #hide lại kết quả nhiều quá
names(cfa)
## [1] "data" "measurement_model" "factor_loadings"
## [4] "constructs" "construct_scores" "item_weights"
## [7] "lavaan_model" "lavaan_output"
summary(cfa)
##
## Results from package seminr (2.3.2)
## Estimation used package seminr (2.3.2)
##
## Fit metrics:
## npar fmin logl aic bic ntotal bic2 rmr
## 8.40e+01 5.88e-01 -3.34e+04 6.70e+04 6.74e+04 5.69e+02 6.71e+04 6.36e-02
## srmr crmr gfi agfi pgfi mfi ecvi
## 3.09e-02 3.17e-02 9.41e-01 9.33e-01 8.28e-01 9.57e-01 1.47e+00
## metric scaled robust
## cfi 9.94e-01 9.96e-01 9.97e-01
## tli 9.93e-01 9.96e-01 9.96e-01
## nnfi 9.93e-01 9.96e-01 9.96e-01
## rni 9.94e-01 9.96e-01 9.97e-01
## rmsea 1.19e-02 8.51e-03 8.67e-03
## rmsea.ci.lower 0.00e+00 0.00e+00 0.00e+00
## rmsea.ci.upper 1.82e-02 1.59e-02 1.63e-02
## rmsea.pvalue 1.00e+00 1.00e+00 1.00e+00
## rmsea.notclose.pvalue 2.04e-202 0.00e+00 2.37e-199
## chisq 6.69e+02 6.44e+02 NA
## df 6.19e+02 6.19e+02 NA
## pvalue 8.10e-02 2.32e-01 NA
## baseline.chisq 8.76e+03 7.87e+03 NA
## baseline.df 6.66e+02 6.66e+02 NA
## baseline.pvalue 0.00e+00 0.00e+00 NA
## rfi 9.18e-01 9.12e-01 NA
## nfi 9.24e-01 9.18e-01 NA
## pnfi 8.58e-01 8.53e-01 NA
## ifi 9.94e-01 9.96e-01 NA
##
## Loadings:
## $coefficients
## X1 X2 X3 X4 X5
## OIBB1 0.72 . . . .
## OIBB2 0.65 . . . .
## OIBB3 0.71 . . . .
## OIBB4 0.69 . . . .
## OIBB5 0.67 . . . .
## SM1 . 0.65 . . .
## SM2 . 0.69 . . .
## SM3 . 0.74 . . .
## SM4 . 0.70 . . .
## SM5 . 0.71 . . .
## HM1 . . 0.72 . .
## HM2 . . 0.68 . .
## HM3 . . 0.65 . .
## HM4 . . 0.72 . .
## HM5 . . 0.70 . .
## IST1 . . . 0.64 .
## IST2 . . . 0.66 .
## IST4 . . . 0.67 .
## IST5 . . . 0.67 .
## IST6 . . . 0.72 .
## IST7 . . . 0.67 .
## IST8 . . . 0.66 .
## IST9 . . . 0.71 .
## IST10 . . . 0.76 .
## IST11 . . . 0.69 .
## IST12 . . . 0.38 .
## SI1 . . . . 0.71
## SI2 . . . . 0.70
## SI3 . . . . 0.70
## SI4 . . . . 0.72
## SI5 . . . . 0.72
## SI6 . . . . 0.66
## SI9 . . . . 0.73
## SI12 . . . . 0.73
## SI13 . . . . 0.69
## SI14 . . . . 0.67
## SI15 . . . . 0.69
##
## $significance
## Std Estimate SE t-Value 2.5% CI 97.5% CI
## X1 -> OIBB1 0.72 0.034 0 0.65 0.79
## X1 -> OIBB2 0.65 0.037 0 0.58 0.73
## X1 -> OIBB3 0.71 0.036 0 0.64 0.78
## X1 -> OIBB4 0.69 0.036 0 0.62 0.76
## X1 -> OIBB5 0.67 0.036 0 0.60 0.74
## X2 -> SM1 0.65 0.039 0 0.57 0.72
## X2 -> SM2 0.69 0.036 0 0.62 0.76
## X2 -> SM3 0.74 0.037 0 0.67 0.81
## X2 -> SM4 0.70 0.036 0 0.63 0.77
## X2 -> SM5 0.71 0.036 0 0.64 0.78
## X3 -> HM1 0.72 0.034 0 0.65 0.78
## X3 -> HM2 0.68 0.039 0 0.60 0.75
## X3 -> HM3 0.65 0.038 0 0.57 0.73
## X3 -> HM4 0.72 0.035 0 0.65 0.79
## X3 -> HM5 0.70 0.035 0 0.63 0.77
## X4 -> IST1 0.64 0.037 0 0.57 0.71
## X4 -> IST2 0.66 0.037 0 0.59 0.73
## X4 -> IST4 0.67 0.036 0 0.60 0.74
## X4 -> IST5 0.67 0.036 0 0.60 0.74
## X4 -> IST6 0.72 0.033 0 0.65 0.78
## X4 -> IST7 0.67 0.036 0 0.60 0.74
## X4 -> IST8 0.66 0.036 0 0.59 0.73
## X4 -> IST9 0.71 0.034 0 0.65 0.78
## X4 -> IST10 0.76 0.031 0 0.69 0.82
## X4 -> IST11 0.69 0.035 0 0.62 0.76
## X4 -> IST12 0.38 0.043 0 0.30 0.46
## X5 -> SI1 0.71 0.031 0 0.65 0.77
## X5 -> SI2 0.70 0.033 0 0.63 0.76
## X5 -> SI3 0.70 0.032 0 0.64 0.77
## X5 -> SI4 0.72 0.033 0 0.65 0.78
## X5 -> SI5 0.72 0.032 0 0.66 0.78
## X5 -> SI6 0.66 0.036 0 0.59 0.73
## X5 -> SI9 0.73 0.033 0 0.66 0.79
## X5 -> SI12 0.73 0.032 0 0.66 0.79
## X5 -> SI13 0.69 0.035 0 0.62 0.76
## X5 -> SI14 0.67 0.035 0 0.61 0.74
## X5 -> SI15 0.69 0.034 0 0.63 0.76
plot(cfa)
## NULL
3.2 Chạy CB-SEM
cbsem <- estimate_cbsem(
data = dulieu,
measurement_model = as.reflective(thangdo),
structural_model = moiquanhe
)
#cbsem
names(cbsem)
## [1] "data" "rawdata" "measurement_model"
## [4] "factor_loadings" "associations" "mmMatrix"
## [7] "smMatrix" "constructs" "construct_scores"
## [10] "item_weights" "path_coef" "lavaan_model"
## [13] "lavaan_output"
summary(cbsem)
##
## Results from package seminr (2.3.2)
## Estimation used package seminr (2.3.2)
##
## Fit metrics:
## npar fmin logl aic bic ntotal bic2
## 94.000 0.648 -35061.839 70311.679 70720.003 569.000 70421.596
## rmr srmr crmr gfi agfi pgfi mfi
## 0.089 0.044 0.045 0.938 0.930 0.825 0.955
## ecvi
## 1.627
##
## metric scaled robust
## cfi 0.994 0.995 0.995
## tli 0.993 0.994 0.995
## nnfi 0.993 0.994 0.995
## rni 0.994 0.995 0.995
## rmsea 0.012 0.010 0.010
## rmsea.ci.lower 0.000 0.000 0.000
## rmsea.ci.upper 0.018 0.016 0.017
## rmsea.pvalue 1.000 1.000 1.000
## rmsea.notclose.pvalue 0.000 0.000 0.000
## chisq 737.804 723.660 .
## df 686.000 686.000 .
## pvalue 0.083 0.155 .
## baseline.chisq 8885.984 8091.958 .
## baseline.df 741.000 741.000 .
## baseline.pvalue 0.000 0.000 .
## rfi 0.910 0.903 .
## nfi 0.917 0.911 .
## pnfi 0.849 0.843 .
## ifi 0.994 0.995 .
##
## Reliability:
## rhoC AVE
## X1 0.82 0.47
## X2 0.83 0.49
## X3 0.82 0.48
## X4 0.89 0.44
## X5 0.91 0.49
##
## Path Coefficients:
## X1 X4
## R^2 0.17 0.07
## X2 0.17 0.16
## X3 0.15 0.19
## X4 0.17 .
## X5 0.12 .
## X2_x_X5 -0.10 .
## X3_x_X5 -0.07 .
plot(cbsem)
## NULL
3.3 Chạy PLS-SEM
plssem <-estimate_pls(
data=dulieu,
measurement_model = thangdo,
structural_model = moiquanhe
)
names(plssem)
## [1] "meanData" "sdData" "smMatrix"
## [4] "mmMatrix" "constructs" "mmVariables"
## [7] "outer_loadings" "outer_weights" "path_coef"
## [10] "iterations" "weightDiff" "construct_scores"
## [13] "rSquared" "inner_weights" "data"
## [16] "rawdata" "measurement_model" "structural_model"
## [19] "settings" "interaction"
summary(plssem)
##
## Results from package seminr (2.3.2)
##
## Path Coefficients:
## X1 X4
## R^2 0.141 0.055
## AdjR^2 0.132 0.052
## X2 0.144 0.145
## X3 0.134 0.162
## X4 0.147 .
## X5 0.118 .
## X2*X5 -0.085 .
## X3*X5 -0.078 .
##
## Reliability:
## alpha rhoC AVE rhoA
## X2 0.826 0.878 0.589 0.834
## X3 0.821 0.874 0.582 0.829
## X4 0.893 0.912 0.489 0.902
## X5 0.915 0.928 0.538 0.921
## X2*X5 1.000 1.000 1.000 1.000
## X3*X5 1.000 1.000 1.000 1.000
## X1 0.819 0.873 0.580 0.823
##
## Alpha, rhoC, and rhoA should exceed 0.7 while AVE should exceed 0.5
plot(plssem)
Chạy bootstrap
bootpls <- bootstrap_model(seminr_model = plssem,
nboot = 1000,
cores = 2)
names(bootpls)
## [1] "meanData" "sdData"
## [3] "smMatrix" "mmMatrix"
## [5] "constructs" "mmVariables"
## [7] "outer_loadings" "outer_weights"
## [9] "path_coef" "iterations"
## [11] "weightDiff" "construct_scores"
## [13] "rSquared" "inner_weights"
## [15] "data" "rawdata"
## [17] "measurement_model" "structural_model"
## [19] "settings" "interaction"
## [21] "boot_paths" "boot_loadings"
## [23] "boot_weights" "boot_HTMT"
## [25] "boot_total_paths" "paths_descriptives"
## [27] "loadings_descriptives" "weights_descriptives"
## [29] "HTMT_descriptives" "total_paths_descriptives"
## [31] "boots" "seed"
summary(bootpls)
##
## Results from Bootstrap resamples: 1000
##
## Bootstrapped Structural Paths:
## Original Est. Bootstrap Mean Bootstrap SD T Stat. 2.5% CI
## X2 -> X4 0.145 0.150 0.042 3.438 0.068
## X2 -> X1 0.144 0.148 0.042 3.463 0.067
## X3 -> X4 0.162 0.167 0.042 3.857 0.084
## X3 -> X1 0.134 0.135 0.046 2.927 0.048
## X4 -> X1 0.147 0.148 0.043 3.402 0.070
## X5 -> X1 0.118 0.128 0.037 3.189 0.060
## X2*X5 -> X1 -0.085 -0.086 0.041 -2.055 -0.166
## X3*X5 -> X1 -0.078 -0.078 0.041 -1.891 -0.157
## 97.5% CI
## X2 -> X4 0.232
## X2 -> X1 0.231
## X3 -> X4 0.247
## X3 -> X1 0.223
## X4 -> X1 0.238
## X5 -> X1 0.199
## X2*X5 -> X1 -0.005
## X3*X5 -> X1 0.001
##
## Bootstrapped Weights:
## Original Est. Bootstrap Mean Bootstrap SD T Stat.
## OIBB1 -> X1 0.239 0.241 0.025 9.529
## OIBB2 -> X1 0.234 0.234 0.028 8.442
## OIBB3 -> X1 0.295 0.295 0.025 11.651
## OIBB4 -> X1 0.283 0.280 0.025 11.408
## OIBB5 -> X1 0.260 0.260 0.024 10.916
## SM1 -> X2 0.222 0.220 0.043 5.101
## SM2 -> X2 0.290 0.290 0.041 7.100
## SM3 -> X2 0.259 0.261 0.034 7.527
## SM4 -> X2 0.228 0.226 0.043 5.316
## SM5 -> X2 0.300 0.299 0.040 7.572
## HM1 -> X3 0.246 0.245 0.038 6.520
## HM2 -> X3 0.247 0.250 0.038 6.556
## HM3 -> X3 0.278 0.276 0.038 7.401
## HM4 -> X3 0.316 0.316 0.038 8.280
## HM5 -> X3 0.221 0.218 0.041 5.449
## IST1 -> X4 0.150 0.149 0.021 7.087
## IST2 -> X4 0.151 0.151 0.020 7.449
## IST4 -> X4 0.107 0.107 0.018 5.891
## IST5 -> X4 0.118 0.118 0.019 6.132
## IST6 -> X4 0.143 0.143 0.017 8.499
## IST7 -> X4 0.128 0.127 0.019 6.703
## IST8 -> X4 0.142 0.140 0.019 7.469
## IST9 -> X4 0.141 0.141 0.017 8.242
## IST10 -> X4 0.149 0.149 0.016 9.155
## IST11 -> X4 0.112 0.112 0.019 5.944
## IST12 -> X4 0.075 0.076 0.025 2.973
## SI1 -> X5 0.126 0.125 0.030 4.217
## SI2 -> X5 0.168 0.168 0.031 5.479
## SI3 -> X5 0.148 0.148 0.027 5.466
## SI4 -> X5 0.099 0.099 0.030 3.347
## SI5 -> X5 0.082 0.079 0.032 2.592
## SI6 -> X5 0.135 0.135 0.030 4.532
## SI9 -> X5 0.112 0.111 0.029 3.905
## SI12 -> X5 0.147 0.148 0.031 4.708
## SI13 -> X5 0.104 0.101 0.028 3.674
## SI14 -> X5 0.111 0.112 0.030 3.701
## SI15 -> X5 0.128 0.129 0.029 4.434
## X2*X5_intxn -> X2*X5 1.000 1.000 0.000 .
## X3*X5_intxn -> X3*X5 1.000 1.000 0.000 .
## 2.5% CI 97.5% CI
## OIBB1 -> X1 0.192 0.291
## OIBB2 -> X1 0.181 0.291
## OIBB3 -> X1 0.249 0.349
## OIBB4 -> X1 0.230 0.329
## OIBB5 -> X1 0.216 0.305
## SM1 -> X2 0.128 0.305
## SM2 -> X2 0.211 0.377
## SM3 -> X2 0.191 0.329
## SM4 -> X2 0.135 0.307
## SM5 -> X2 0.225 0.376
## HM1 -> X3 0.168 0.318
## HM2 -> X3 0.176 0.319
## HM3 -> X3 0.204 0.353
## HM4 -> X3 0.245 0.396
## HM5 -> X3 0.128 0.291
## IST1 -> X4 0.108 0.192
## IST2 -> X4 0.113 0.193
## IST4 -> X4 0.070 0.140
## IST5 -> X4 0.081 0.157
## IST6 -> X4 0.110 0.176
## IST7 -> X4 0.086 0.164
## IST8 -> X4 0.101 0.176
## IST9 -> X4 0.107 0.175
## IST10 -> X4 0.117 0.181
## IST11 -> X4 0.072 0.146
## IST12 -> X4 0.026 0.129
## SI1 -> X5 0.068 0.184
## SI2 -> X5 0.117 0.234
## SI3 -> X5 0.099 0.206
## SI4 -> X5 0.037 0.153
## SI5 -> X5 0.008 0.132
## SI6 -> X5 0.079 0.195
## SI9 -> X5 0.050 0.166
## SI12 -> X5 0.088 0.217
## SI13 -> X5 0.043 0.150
## SI14 -> X5 0.048 0.172
## SI15 -> X5 0.075 0.188
## X2*X5_intxn -> X2*X5 1.000 1.000
## X3*X5_intxn -> X3*X5 1.000 1.000
##
## Bootstrapped Loadings:
## Original Est. Bootstrap Mean Bootstrap SD T Stat.
## OIBB1 -> X1 0.768 0.768 0.028 27.351
## OIBB2 -> X1 0.728 0.726 0.033 22.151
## OIBB3 -> X1 0.786 0.785 0.025 31.204
## OIBB4 -> X1 0.771 0.770 0.027 28.200
## OIBB5 -> X1 0.752 0.752 0.027 27.527
## SM1 -> X2 0.718 0.715 0.040 17.824
## SM2 -> X2 0.776 0.774 0.030 25.631
## SM3 -> X2 0.789 0.788 0.030 26.467
## SM4 -> X2 0.756 0.753 0.036 21.240
## SM5 -> X2 0.796 0.793 0.029 27.217
## HM1 -> X3 0.768 0.766 0.030 25.733
## HM2 -> X3 0.749 0.750 0.035 21.395
## HM3 -> X3 0.748 0.746 0.031 24.071
## HM4 -> X3 0.800 0.800 0.026 30.282
## HM5 -> X3 0.748 0.745 0.036 20.942
## IST1 -> X4 0.696 0.694 0.033 21.044
## IST2 -> X4 0.710 0.709 0.032 22.277
## IST4 -> X4 0.696 0.694 0.035 20.048
## IST5 -> X4 0.703 0.701 0.035 20.135
## IST6 -> X4 0.749 0.750 0.028 26.603
## IST7 -> X4 0.706 0.703 0.033 21.378
## IST8 -> X4 0.703 0.700 0.033 21.144
## IST9 -> X4 0.744 0.742 0.030 25.118
## IST10 -> X4 0.782 0.782 0.025 31.697
## IST11 -> X4 0.716 0.714 0.033 21.949
## IST12 -> X4 0.422 0.424 0.048 8.788
## SI1 -> X5 0.744 0.741 0.032 23.308
## SI2 -> X5 0.752 0.752 0.028 26.873
## SI3 -> X5 0.742 0.741 0.028 26.336
## SI4 -> X5 0.733 0.730 0.036 20.611
## SI5 -> X5 0.729 0.725 0.035 20.919
## SI6 -> X5 0.709 0.707 0.033 21.612
## SI9 -> X5 0.750 0.747 0.033 22.692
## SI12 -> X5 0.761 0.762 0.030 25.352
## SI13 -> X5 0.716 0.711 0.034 20.938
## SI14 -> X5 0.700 0.699 0.035 19.748
## SI15 -> X5 0.729 0.728 0.032 22.833
## X2*X5_intxn -> X2*X5 1.052 1.051 0.028 37.700
## X3*X5_intxn -> X3*X5 1.055 1.053 0.027 38.541
## 2.5% CI 97.5% CI
## OIBB1 -> X1 0.710 0.819
## OIBB2 -> X1 0.662 0.786
## OIBB3 -> X1 0.732 0.830
## OIBB4 -> X1 0.710 0.817
## OIBB5 -> X1 0.695 0.803
## SM1 -> X2 0.625 0.785
## SM2 -> X2 0.707 0.825
## SM3 -> X2 0.726 0.842
## SM4 -> X2 0.676 0.815
## SM5 -> X2 0.729 0.843
## HM1 -> X3 0.702 0.821
## HM2 -> X3 0.679 0.812
## HM3 -> X3 0.680 0.804
## HM4 -> X3 0.746 0.848
## HM5 -> X3 0.658 0.805
## IST1 -> X4 0.632 0.755
## IST2 -> X4 0.644 0.767
## IST4 -> X4 0.621 0.757
## IST5 -> X4 0.627 0.765
## IST6 -> X4 0.691 0.800
## IST7 -> X4 0.637 0.762
## IST8 -> X4 0.632 0.759
## IST9 -> X4 0.680 0.798
## IST10 -> X4 0.730 0.829
## IST11 -> X4 0.647 0.772
## IST12 -> X4 0.323 0.519
## SI1 -> X5 0.676 0.799
## SI2 -> X5 0.691 0.804
## SI3 -> X5 0.684 0.795
## SI4 -> X5 0.658 0.794
## SI5 -> X5 0.649 0.785
## SI6 -> X5 0.637 0.767
## SI9 -> X5 0.680 0.806
## SI12 -> X5 0.701 0.814
## SI13 -> X5 0.642 0.771
## SI14 -> X5 0.624 0.760
## SI15 -> X5 0.665 0.785
## X2*X5_intxn -> X2*X5 0.996 1.106
## X3*X5_intxn -> X3*X5 1.001 1.104
##
## Bootstrapped HTMT:
## Original Est. Bootstrap Mean Bootstrap SD 2.5% CI 97.5% CI
## X2 -> X3 0.207 0.209 0.052 0.116 0.311
## X2 -> X4 0.197 0.203 0.044 0.126 0.289
## X2 -> X5 0.150 0.159 0.041 0.091 0.251
## X2 -> X2*X5 0.030 0.055 0.026 0.022 0.120
## X2 -> X3*X5 0.133 0.132 0.049 0.044 0.226
## X2 -> X1 0.261 0.263 0.050 0.163 0.362
## X3 -> X4 0.212 0.216 0.046 0.133 0.307
## X3 -> X5 0.211 0.211 0.047 0.122 0.306
## X3 -> X2*X5 0.129 0.129 0.047 0.049 0.224
## X3 -> X3*X5 0.034 0.061 0.031 0.019 0.141
## X3 -> X1 0.262 0.263 0.052 0.162 0.374
## X4 -> X5 0.227 0.231 0.046 0.145 0.324
## X4 -> X2*X5 0.116 0.118 0.041 0.047 0.196
## X4 -> X3*X5 0.129 0.132 0.046 0.051 0.224
## X4 -> X1 0.275 0.279 0.047 0.188 0.375
## X5 -> X2*X5 0.033 0.059 0.026 0.029 0.131
## X5 -> X3*X5 0.027 0.058 0.025 0.027 0.123
## X5 -> X1 0.207 0.212 0.045 0.127 0.301
## X2*X5 -> X3*X5 0.201 0.197 0.072 0.048 0.336
## X2*X5 -> X1 0.145 0.149 0.045 0.067 0.242
## X3*X5 -> X1 0.152 0.154 0.048 0.064 0.247
##
## Bootstrapped Total Paths:
## Original Est. Bootstrap Mean Bootstrap SD 2.5% CI 97.5% CI
## X2 -> X4 0.145 0.150 0.042 0.068 0.232
## X2 -> X1 0.165 0.171 0.041 0.090 0.254
## X3 -> X4 0.162 0.167 0.042 0.084 0.247
## X3 -> X1 0.157 0.160 0.045 0.075 0.248
## X4 -> X1 0.147 0.148 0.043 0.070 0.238
## X5 -> X1 0.118 0.128 0.037 0.060 0.199
## X2*X5 -> X1 -0.085 -0.086 0.041 -0.166 -0.005
## X3*X5 -> X1 -0.078 -0.078 0.041 -0.157 0.001
plot(bootpls)