Update the WAIS-III Model

Structural Equation Modeling with lavaan in R

Erin Buchanan

Professor

Three-Factor WAIS-III

semPaths(object = wais.fit, layout = "tree", rotation = 1,
          whatLabels = "std", edge.label.cex = 1,
          what = "std", edge.color = "black")

Three Factor WAIS Diagram from semPaths()

Factor Loadings

summary(wais.fit, standardized = TRUE, fit.measures = TRUE)

Latent Variables:
          Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  verbalcomp =~                                                         
    vocab    1.000                               6.281    0.879
    simil    0.296    0.031    9.483    0.000    1.861    0.581
    inform   0.449    0.043   10.481    0.000    2.822    0.644
    compreh  0.315    0.035    8.999    0.000    1.981    0.552
  workingmemory =~                                                      
    arith    1.000                               2.528    0.844
    digspan  0.881    0.152    5.786    0.000    2.227    0.565
    lnseq    0.205    0.107    1.920    0.055    0.518    0.129
                               - - -

Variances

Variances:
                Estimate  Std.Err z-value P(>|z|)  Std.lv Std.all
                               - - - 
   .piccomp       3.138    0.317   9.913   0.000   3.138   0.577
   .block        27.343    3.226   8.476   0.000  27.343   0.459
   .matrixreason  4.960    0.441  11.243   0.000   4.960   0.757
   .digsym      132.291   10.925  12.109   0.000 132.291   0.957
                               - - -

var(IQdata$digsym)

138.665

Fit Indices

User model versus baseline model:
  Comparative Fit Index (CFI)                    0.793
  Tucker-Lewis Index (TLI)                       0.733

Root Mean Square Error of Approximation:
  RMSEA                                          0.115
  90 Percent Confidence Interval          0.101  0.129
  P-value RMSEA <= 0.05                          0.000

Standardized Root Mean Square Residual:
  SRMR                                           0.076

Modification Indices

modificationindices(wais.fit, sort = TRUE)
              lhs op          rhs     mi     epc sepc.lv sepc.all sepc.nox
66          simil ~~       inform 35.879  -3.757  -3.757   -0.268   -0.268
56          vocab ~~       inform 28.377   9.783   9.783    0.313    0.313
48     perceptorg =~        vocab 21.865  -2.077  -3.151   -0.441   -0.441
115         block ~~ matrixreason 16.209  -3.622  -3.622   -0.183   -0.183
96          arith ~~        block 15.061   3.679   3.679    0.159    0.159
117         block ~~ symbolsearch 13.144   5.725   5.725    0.180    0.180
47  workingmemory =~ symbolsearch 12.272  -0.467  -1.181   -0.286   -0.286
81         inform ~~        block 12.269   4.358   4.358    0.129    0.129
64          vocab ~~       digsym 11.578 -11.261 -11.261   -0.134   -0.134
40  workingmemory =~        simil 11.383   0.278   0.703    0.220    0.220
72          simil ~~        block 10.605  -3.084  -3.084   -0.125   -0.125
45  workingmemory =~ matrixreason  9.685   0.267   0.675    0.264    0.264

Let's practice!

Structural Equation Modeling with lavaan in R