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1 PLS-Power Analysis

已有 537 次阅读 2022-3-1 09:32 |个人分类:power analysis|系统分类:科研笔记

编码如下:


library(devtools)

library(lavaan)

library(snow)

library(simsem)

library(matrixpls)

model<-"! regressions

A=~0.753*x1

A=~0.757*x2

A=~0.812*x3

A=~0.830*x4

B=~0.842*x5

B=~0.812*x6

B=~0.905*x7

C=~0.743*x8

C=~0.789*x9

C=~0.822*x10

D=~0.807*x11

D=~0.747*x12

D=~0.722*X13

E=~0.817*X14

E=~0.821*X15

E=~0.764*X16

E=~0.706*X17

F=~0.855*X18

F=~0.848*X19

F=~0.802*X20

G=~0.854*X21

G=~0.841*X22

G=~0.832*X23

H=~0.877*X24

H=~0.759*X25

H=~0.861*X26

G ~ 0.142*A

G ~ 0.059*B

G ~ 0.179*C

G ~ 0.264*D

G ~ 0.071*E

G ~ 0.193*F

H ~ 0.639*G

! residuals, variances and covariances

A ~~ 1.0*A

B ~~ 1.0*B

C ~~ 1.0*C

D ~~ 1.0*D

E ~~ 1.0*E

F ~~ 1.0*F

G ~~ 0.556*G

H ~~ 0.591*H

B ~~ 0.336*A

C ~~ 0.354*A

D ~~ 0.361*A

E ~~ 0.386*A

F ~~ 0.309*A

C ~~ 0.228*B

D ~~ 0.282*B

E ~~ 0.355*B

F ~~ 0.266*B

D ~~ 0.523*C

E ~~ 0.531*C

F ~~ 0.393*C

E ~~ 0.567*D

F ~~ 0.482*D

F ~~ 0.630*E

x1 ~~ 0.433*x1

x2 ~~ 0.427*x2

x3 ~~ 0.341*x3

x4 ~~ 0.311*x4

x5 ~~ 0.291*x5

x6 ~~ 0.341*x6

x7 ~~ 0.181*x7

x8 ~~ 0.448*x8

x9 ~~ 0.377*x9

x10 ~~ 0.324*x10

x11 ~~ 0.349*x11

x12 ~~ 0.442*x12

x13 ~~ 0.479*x13

x14 ~~ 0.333*x14

x15 ~~ 0.326*x15

x16 ~~ 0.416*x16

x17 ~~ 0.502*x17

x18 ~~ 0.269*x18

x19 ~~ 0.281*x19

x20 ~~ 0.357*x20

x21 ~~ 0.271*x21

x22 ~~ 0.293*x22

x23 ~~ 0.308*x23

x24 ~~ 0.231*x24

x25 ~~ 0.424*x25

x26 ~~ 0.259*x26"

# Normal data

output <- matrixpls.sim(1000, model, n=376, multicore=FALSE, completeRep = TRUE)

summary(output)




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