Modification Indices

R में lavaan के साथ Structural Equation Modeling

Erin Buchanan

Professor

कमज़ोर मॉडल अपडेट करना

User model versus baseline model:
  Comparative Fit Index (CFI)                    0.879
  Tucker-Lewis Index (TLI)                       0.774

Root Mean Square Error of Approximation:
  RMSEA                                          0.128
  90 Percent Confidence Interval          0.094  0.164
  P-value RMSEA <= 0.05                          0.000

Standardized Root Mean Square Residual:
  SRMR                                           0.079

कमज़ोर मॉडल अपडेट करना (2)

Latent Variables:
          Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  visual =~                                                             
    x1       1.000                               0.777    0.667
    x2       0.690    0.124    5.585    0.000    0.536    0.456
    x3       0.985    0.160    6.157    0.000    0.766    0.678
  speed =~                                                              
    x7       1.000                               0.622    0.572
    x8       1.204    0.170    7.090    0.000    0.749    0.741
    x9       1.052    0.147    7.142    0.000    0.654    0.649

कमज़ोर मॉडल अपडेट करना (3)

Variances:
          Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .x1      0.754    0.110    6.838    0.000    0.754    0.555
   .x2      1.094    0.103   10.661    0.000    1.094    0.792
   .x3      0.688    0.105    6.557    0.000    0.688    0.540
   .x7      0.796    0.082    9.756    0.000    0.796    0.673
   .x8      0.461    0.077    6.002    0.000    0.461    0.451
   .x9      0.587    0.071    8.273    0.000    0.587    0.578

var(HolzingerSwineford1939$x1)

1.362898

Modification Indices

modificationindices(twofactor.fit, sort = TRUE)

      lhs op rhs     mi    epc sepc.lv sepc.all sepc.nox
34     x7 ~~  x8 35.521  0.624   0.624    0.568    0.568
18 visual =~  x9 35.521  0.659   0.512    0.508    0.508
36     x8 ~~  x9 19.041 -0.527  -0.527   -0.517   -0.517
16 visual =~  x7 19.041 -0.503  -0.391   -0.359   -0.359
26     x1 ~~  x9 11.428  0.177   0.177    0.151    0.151

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मॉडल अपडेट करना

34     x7 ~~  x8 35.521  0.624   0.624    0.568    0.568

twofactor.model <- 'visual =~ x1 + x2 + x3 
                        speed =~ x7 + x8 + x9 
                        x7 ~~ x8'
twofactor.fit <- cfa(model = twofactor.model,
                     data = HolzingerSwineford1939)
summary(twofactor.fit, standardized = TRUE, 
        fit.measures = TRUE)

User model versus baseline model:
  Comparative Fit Index (CFI)                    0.976
  Tucker-Lewis Index (TLI)                       0.949

अभ्यास करते हैं!

R में lavaan के साथ Structural Equation Modeling