A simulated dataset.
syntax <- '
f =~ y1 + y2 + y3
f ~ x1 + x2 + x3 + w1 + w2 + (1 | cluster)
'
fit <- pls(syntax, data = randomInterceptsOrdered)
summary(fit)
#> plssem->fitMeasures():
#> Fit measures for MC-PLSc models are under development! Traditional fit
#> criteria will likely be too strict.
#> plssem->fitMeasures():
#> Resampling MC-PLSc Model (R = 1000000)...
#> plssem (0.1.3) ended normally after 63 iterations
#> Estimator MCOrdPLSc-MLM
#> Link PROBIT
#>
#> Number of observations 10000
#> Number of iterations 63
#> Number of latent variables 1
#> Number of observed variables 9
#>
#> Fit Measures:
#> Chi-Square 10.924
#> Degrees of Freedom 10
#> SRMR 0.003
#> RMSEA 0.003
#>
#> R-squared (indicators):
#> y1 0.880
#> y2 0.789
#> y3 0.815
#>
#> R-squared (latents):
#> f 0.121
#>
#> Latent Variables:
#> Estimate Std.Error z.value P(>|z|)
#> f =~
#> y1 0.938
#> y2 0.888
#> y3 0.903
#>
#> Regressions:
#> Estimate Std.Error z.value P(>|z|)
#> f ~
#> x1 0.240
#> x2 0.159
#> x3 0.081
#> w1 0.123
#> w2 0.078
#>
#> Covariances:
#> Estimate Std.Error z.value P(>|z|)
#> x1 ~~
#> x2 0.110
#> x3 0.012
#> w1 0.001
#> w2 0.002
#> x2 ~~
#> x3 0.100
#> w1 -0.003
#> w2 -0.001
#> x3 ~~
#> w1 -0.002
#> w2 0.004
#> w1 ~~
#> w2 -0.027
#>
#> Thresholds:
#> Estimate Std.Error z.value P(>|z|)
#> y1|t1 -2.658
#> y1|t2 -1.793
#> y1|t3 -0.422
#> y1|t4 0.329
#> y1|t5 1.307
#> y1|t6 2.357
#> y2|t1 -2.881
#> y2|t2 -1.919
#> y2|t3 -0.979
#> y2|t4 0.185
#> y2|t5 1.050
#> y2|t6 2.224
#> y3|t1 -2.276
#> y3|t2 -1.260
#> y3|t3 0.013
#> y3|t4 0.697
#> y3|t5 1.789
#> y3|t6 2.820
#> x1|t1 -2.361
#> x1|t2 -1.342
#> x1|t3 -0.670
#> x1|t4 0.489
#> x1|t5 1.532
#> x1|t6 2.644
#> x2|t1 -2.884
#> x2|t2 -2.039
#> x2|t3 -1.008
#> x2|t4 -0.117
#> x2|t5 0.813
#> x2|t6 1.896
#> x3|t1 -3.018
#> x3|t2 -1.918
#> x3|t3 -0.842
#> x3|t4 -0.160
#> x3|t5 1.006
#> x3|t6 2.237
#> w1|t1 -2.747
#> w1|t2 -2.024
#> w1|t3 -0.965
#> w1|t4 0.120
#> w1|t5 1.228
#> w1|t6 2.624
#> w2|t1 -1.971
#> w2|t2 -0.952
#> w2|t3 -0.119
#> w2|t4 0.739
#> w2|t5 1.823
#> w2|t6 2.484
#>
#> Variances:
#> Estimate Std.Error z.value P(>|z|)
#> .f 0.879
#> x1 1.000
#> x2 1.000
#> x3 1.000
#> w1 1.000
#> w2 1.000
#> .y1 0.120
#> .y2 0.211
#> .y3 0.185
#> f~1 0.619
#>