Tidy report of lavaan model.
Usage
lavaan_summary(
lavaan,
ci = c("raw", "boot", "bc.boot", "bca.boot"),
nsim = 100,
seed = NULL,
digits = 3,
print = TRUE,
covariance = FALSE,
file = NULL
)Arguments
- lavaan
Model object fitted by
lavaan.- ci
Method for estimating standard error (SE) and 95% confidence interval (CI).
Defaults to
"raw"(the standard approach oflavaan). Other options:"boot"Percentile Bootstrap
"bc.boot"Bias-Corrected Percentile Bootstrap
"bca.boot"Bias-Corrected and Accelerated (BCa) Percentile Bootstrap
- nsim
Number of simulation samples (bootstrap resampling) for estimating SE and 95% CI. In formal analyses,
nsim=1000(or larger) is strongly suggested.- seed
Random seed for obtaining reproducible results. Defaults to
NULL.- digits
Number of decimal places of output. Defaults to
3.Print results. Defaults to
TRUE.- covariance
Print (co)variances. Defaults to
FALSE.- file
File name of MS Word (
.doc).
Value
Invisibly return a list of results:
fitModel fit indices.
measureLatent variable measures.
regressionRegression paths.
covarianceVariances and/or covariances.
effectDefined effect estimates.
Examples
## Simple Mediation:
## Solar.R (X) => Ozone (M) => Temp (Y)
# PROCESS(airquality, y="Temp", x="Solar.R",
# meds="Ozone", ci="boot", nsim=1000, seed=1)
model = "
Ozone ~ a*Solar.R
Temp ~ c.*Solar.R + b*Ozone
Indirect := a*b
Direct := c.
Total := c. + a*b
"
lv = lavaan::sem(model=model, data=airquality)
lavaan::summary(lv, fit.measure=TRUE, ci=TRUE, nd=3) # raw output
#> lavaan 0.6.16 ended normally after 1 iteration
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 5
#>
#> Used Total
#> Number of observations 111 153
#>
#> Model Test User Model:
#>
#> Test statistic 0.000
#> Degrees of freedom 0
#>
#> Model Test Baseline Model:
#>
#> Test statistic 89.294
#> Degrees of freedom 3
#> P-value 0.000
#>
#> User Model versus Baseline Model:
#>
#> Comparative Fit Index (CFI) 1.000
#> Tucker-Lewis Index (TLI) 1.000
#>
#> Loglikelihood and Information Criteria:
#>
#> Loglikelihood user model (H0) -908.632
#> Loglikelihood unrestricted model (H1) -908.632
#>
#> Akaike (AIC) 1827.265
#> Bayesian (BIC) 1840.812
#> Sample-size adjusted Bayesian (SABIC) 1825.011
#>
#> Root Mean Square Error of Approximation:
#>
#> RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: RMSEA <= 0.050 NA
#> P-value H_0: RMSEA >= 0.080 NA
#>
#> Standardized Root Mean Square Residual:
#>
#> SRMR 0.000
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Ozone ~
#> Solar.R (a) 0.127 0.032 3.915 0.000 0.064 0.191
#> Temp ~
#> Solar.R (c.) 0.006 0.008 0.800 0.424 -0.009 0.021
#> Ozone (b) 0.194 0.021 9.390 0.000 0.154 0.235
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> .Ozone 964.164 129.421 7.450 0.000 710.504 1217.825
#> .Temp 45.821 6.151 7.450 0.000 33.766 57.876
#>
#> Defined Parameters:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Indirect 0.025 0.007 3.614 0.000 0.011 0.038
#> Direct 0.006 0.008 0.800 0.424 -0.009 0.021
#> Total 0.031 0.009 3.242 0.001 0.012 0.049
#>
lavaan_summary(lv)
#>
#> Fit Measures (lavaan):
#> χ²(0, N = 111) = 0.000, p = 1.000
#> χ²/df = NaN (saturated model)
#> AIC = 1827.265 (Akaike Information Criterion)
#> BIC = 1840.812 (Bayesian Information Criterion)
#> CFI = 1.000 (Comparative Fit Index)
#> TLI = 1.000 (Tucker-Lewis Index; Non-Normed Fit Index, NNFI)
#> NFI = 1.000 (Normed Fit Index)
#> IFI = 1.000 (Incremental Fit Index)
#> GFI = 1.000 (Goodness-of-Fit Index)
#> AGFI = 1.000 (Adjusted Goodness-of-Fit Index)
#> RMSEA = 0.000, 90% CI [0.000, 0.000] (Root Mean Square Error of Approximation)
#> SRMR = 0.000 (Standardized Root Mean Square Residual)
#>
#> Model Estimates (lavaan):
#> ───────────────────────────────────────────────────────────────────────────
#> Estimate S.E. z p LLCI ULCI Beta
#> ───────────────────────────────────────────────────────────────────────────
#> Regression Paths:
#> Ozone <- Solar.R (a) 0.127 (0.032) 3.915 <.001 *** 0.064 0.191 0.348
#> Temp <- Solar.R (c.) 0.006 (0.008) 0.800 .424 -0.009 0.021 0.058
#> Temp <- Ozone (b) 0.194 (0.021) 9.390 <.001 *** 0.154 0.235 0.678
#> Defined Effects:
#> Indirect 0.025 (0.007) 3.614 <.001 *** 0.011 0.038 0.236
#> Direct 0.006 (0.008) 0.800 .424 -0.009 0.021 0.058
#> Total 0.031 (0.009) 3.242 .001 ** 0.012 0.049 0.294
#> ───────────────────────────────────────────────────────────────────────────
#> Note. Raw (Standard) Confidence Interval (CI) and SE.
#>
# lavaan_summary(lv, ci="boot", nsim=1000, seed=1)
## Serial Multiple Mediation:
## Solar.R (X) => Ozone (M1) => Wind(M2) => Temp (Y)
# PROCESS(airquality, y="Temp", x="Solar.R",
# meds=c("Ozone", "Wind"),
# med.type="serial", ci="boot", nsim=1000, seed=1)
model0 = "
Ozone ~ a1*Solar.R
Wind ~ a2*Solar.R + d12*Ozone
Temp ~ c.*Solar.R + b1*Ozone + b2*Wind
Indirect_All := a1*b1 + a2*b2 + a1*d12*b2
Ind_X_M1_Y := a1*b1
Ind_X_M2_Y := a2*b2
Ind_X_M1_M2_Y := a1*d12*b2
Direct := c.
Total := c. + a1*b1 + a2*b2 + a1*d12*b2
"
lv0 = lavaan::sem(model=model0, data=airquality)
lavaan::summary(lv0, fit.measure=TRUE, ci=TRUE, nd=3) # raw output
#> lavaan 0.6.16 ended normally after 1 iteration
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 9
#>
#> Used Total
#> Number of observations 111 153
#>
#> Model Test User Model:
#>
#> Test statistic 0.000
#> Degrees of freedom 0
#>
#> Model Test Baseline Model:
#>
#> Test statistic 144.974
#> Degrees of freedom 6
#> P-value 0.000
#>
#> User Model versus Baseline Model:
#>
#> Comparative Fit Index (CFI) 1.000
#> Tucker-Lewis Index (TLI) 1.000
#>
#> Loglikelihood and Information Criteria:
#>
#> Loglikelihood user model (H0) -1178.664
#> Loglikelihood unrestricted model (H1) -1178.664
#>
#> Akaike (AIC) 2375.329
#> Bayesian (BIC) 2399.715
#> Sample-size adjusted Bayesian (SABIC) 2371.273
#>
#> Root Mean Square Error of Approximation:
#>
#> RMSEA 0.000
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.000
#> P-value H_0: RMSEA <= 0.050 NA
#> P-value H_0: RMSEA >= 0.080 NA
#>
#> Standardized Root Mean Square Residual:
#>
#> SRMR 0.000
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Ozone ~
#> Solar.R (a1) 0.127 0.032 3.915 0.000 0.064 0.191
#> Wind ~
#> Solar.R (a2) 0.004 0.003 1.234 0.217 -0.002 0.010
#> Ozone (d12) -0.069 0.008 -8.134 0.000 -0.086 -0.052
#> Temp ~
#> Solar.R (c.) 0.007 0.008 0.965 0.334 -0.007 0.022
#> Ozone (b1) 0.172 0.026 6.637 0.000 0.121 0.223
#> Wind (b2) -0.323 0.229 -1.410 0.159 -0.772 0.126
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> .Ozone 964.164 129.421 7.450 0.000 710.504 1217.825
#> .Wind 7.732 1.038 7.450 0.000 5.698 9.766
#> .Temp 45.014 6.042 7.450 0.000 33.172 56.857
#>
#> Defined Parameters:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Indirect_All 0.023 0.007 3.378 0.001 0.010 0.037
#> Ind_X_M1_Y 0.022 0.006 3.372 0.001 0.009 0.035
#> Ind_X_M2_Y -0.001 0.001 -0.928 0.353 -0.004 0.001
#> Ind_X_M1_M2_Y 0.003 0.002 1.309 0.190 -0.001 0.007
#> Direct 0.007 0.008 0.965 0.334 -0.007 0.022
#> Total 0.031 0.009 3.242 0.001 0.012 0.049
#>
lavaan_summary(lv0)
#>
#> Fit Measures (lavaan):
#> χ²(0, N = 111) = 0.000, p = 1.000
#> χ²/df = NaN (saturated model)
#> AIC = 2375.329 (Akaike Information Criterion)
#> BIC = 2399.715 (Bayesian Information Criterion)
#> CFI = 1.000 (Comparative Fit Index)
#> TLI = 1.000 (Tucker-Lewis Index; Non-Normed Fit Index, NNFI)
#> NFI = 1.000 (Normed Fit Index)
#> IFI = 1.000 (Incremental Fit Index)
#> GFI = 1.000 (Goodness-of-Fit Index)
#> AGFI = 1.000 (Adjusted Goodness-of-Fit Index)
#> RMSEA = 0.000, 90% CI [0.000, 0.000] (Root Mean Square Error of Approximation)
#> SRMR = 0.000 (Standardized Root Mean Square Residual)
#>
#> Model Estimates (lavaan):
#> ───────────────────────────────────────────────────────────────────────────────
#> Estimate S.E. z p LLCI ULCI Beta
#> ───────────────────────────────────────────────────────────────────────────────
#> Regression Paths:
#> Ozone <- Solar.R (a1) 0.127 (0.032) 3.915 <.001 *** 0.064 0.191 0.348
#> Wind <- Solar.R (a2) 0.004 (0.003) 1.234 .217 -0.002 0.010 0.098
#> Wind <- Ozone (d12) -0.069 (0.008) -8.134 <.001 *** -0.086 -0.052 -0.647
#> Temp <- Solar.R (c.) 0.007 (0.008) 0.965 .334 -0.007 0.022 0.070
#> Temp <- Ozone (b1) 0.172 (0.026) 6.637 <.001 *** 0.121 0.223 0.600
#> Temp <- Wind (b2) -0.323 (0.229) -1.410 .159 -0.772 0.126 -0.121
#> Defined Effects:
#> Indirect_All 0.023 (0.007) 3.378 <.001 *** 0.010 0.037 0.224
#> Ind_X_M1_Y 0.022 (0.006) 3.372 <.001 *** 0.009 0.035 0.209
#> Ind_X_M2_Y -0.001 (0.001) -0.928 .353 -0.004 0.001 -0.012
#> Ind_X_M1_M2_Y 0.003 (0.002) 1.309 .190 -0.001 0.007 0.027
#> Direct 0.007 (0.008) 0.965 .334 -0.007 0.022 0.070
#> Total 0.031 (0.009) 3.242 .001 ** 0.012 0.049 0.294
#> ───────────────────────────────────────────────────────────────────────────────
#> Note. Raw (Standard) Confidence Interval (CI) and SE.
#>
# lavaan_summary(lv0, ci="boot", nsim=1000, seed=1)
model1 = "
Ozone ~ a1*Solar.R
Wind ~ d12*Ozone
Temp ~ c.*Solar.R + b1*Ozone + b2*Wind
Indirect_All := a1*b1 + a1*d12*b2
Ind_X_M1_Y := a1*b1
Ind_X_M1_M2_Y := a1*d12*b2
Direct := c.
Total := c. + a1*b1 + a1*d12*b2
"
lv1 = lavaan::sem(model=model1, data=airquality)
lavaan::summary(lv1, fit.measure=TRUE, ci=TRUE, nd=3) # raw output
#> lavaan 0.6.16 ended normally after 1 iteration
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 8
#>
#> Used Total
#> Number of observations 111 153
#>
#> Model Test User Model:
#>
#> Test statistic 1.512
#> Degrees of freedom 1
#> P-value (Chi-square) 0.219
#>
#> Model Test Baseline Model:
#>
#> Test statistic 144.974
#> Degrees of freedom 6
#> P-value 0.000
#>
#> User Model versus Baseline Model:
#>
#> Comparative Fit Index (CFI) 0.996
#> Tucker-Lewis Index (TLI) 0.978
#>
#> Loglikelihood and Information Criteria:
#>
#> Loglikelihood user model (H0) -1179.420
#> Loglikelihood unrestricted model (H1) -1178.664
#>
#> Akaike (AIC) 2374.840
#> Bayesian (BIC) 2396.517
#> Sample-size adjusted Bayesian (SABIC) 2371.235
#>
#> Root Mean Square Error of Approximation:
#>
#> RMSEA 0.068
#> 90 Percent confidence interval - lower 0.000
#> 90 Percent confidence interval - upper 0.273
#> P-value H_0: RMSEA <= 0.050 0.281
#> P-value H_0: RMSEA >= 0.080 0.631
#>
#> Standardized Root Mean Square Residual:
#>
#> SRMR 0.028
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Ozone ~
#> Solar.R (a1) 0.127 0.032 3.915 0.000 0.064 0.191
#> Wind ~
#> Ozone (d12) -0.065 0.008 -8.164 0.000 -0.081 -0.050
#> Temp ~
#> Solar.R (c.) 0.007 0.007 0.972 0.331 -0.007 0.022
#> Ozone (b1) 0.172 0.025 6.784 0.000 0.122 0.222
#> Wind (b2) -0.323 0.227 -1.420 0.156 -0.769 0.123
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> .Ozone 964.164 129.421 7.450 0.000 710.504 1217.825
#> .Wind 7.838 1.052 7.450 0.000 5.776 9.900
#> .Temp 45.014 6.042 7.450 0.000 33.172 56.857
#>
#> Defined Parameters:
#> Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
#> Indirect_All 0.025 0.007 3.611 0.000 0.011 0.038
#> Ind_X_M1_Y 0.022 0.006 3.391 0.001 0.009 0.035
#> Ind_X_M1_M2_Y 0.003 0.002 1.317 0.188 -0.001 0.007
#> Direct 0.007 0.007 0.972 0.331 -0.007 0.022
#> Total 0.032 0.009 3.380 0.001 0.013 0.050
#>
lavaan_summary(lv1)
#>
#> Fit Measures (lavaan):
#> χ²(1, N = 111) = 1.512, p = 0.219
#> χ²/df = 1.512
#> AIC = 2374.840 (Akaike Information Criterion)
#> BIC = 2396.517 (Bayesian Information Criterion)
#> CFI = 0.996 (Comparative Fit Index)
#> TLI = 0.978 (Tucker-Lewis Index; Non-Normed Fit Index, NNFI)
#> NFI = 0.990 (Normed Fit Index)
#> IFI = 0.996 (Incremental Fit Index)
#> GFI = 0.991 (Goodness-of-Fit Index)
#> AGFI = 0.911 (Adjusted Goodness-of-Fit Index)
#> RMSEA = 0.068, 90% CI [0.000, 0.273] (Root Mean Square Error of Approximation)
#> SRMR = 0.028 (Standardized Root Mean Square Residual)
#>
#> Model Estimates (lavaan):
#> ───────────────────────────────────────────────────────────────────────────────
#> Estimate S.E. z p LLCI ULCI Beta
#> ───────────────────────────────────────────────────────────────────────────────
#> Regression Paths:
#> Ozone <- Solar.R (a1) 0.127 (0.032) 3.915 <.001 *** 0.064 0.191 0.348
#> Wind <- Ozone (d12) -0.065 (0.008) -8.164 <.001 *** -0.081 -0.050 -0.612
#> Temp <- Solar.R (c.) 0.007 (0.007) 0.972 .331 -0.007 0.022 0.070
#> Temp <- Ozone (b1) 0.172 (0.025) 6.784 <.001 *** 0.122 0.222 0.600
#> Temp <- Wind (b2) -0.323 (0.227) -1.420 .156 -0.769 0.123 -0.120
#> Defined Effects:
#> Indirect_All 0.025 (0.007) 3.611 <.001 *** 0.011 0.038 0.235
#> Ind_X_M1_Y 0.022 (0.006) 3.391 <.001 *** 0.009 0.035 0.209
#> Ind_X_M1_M2_Y 0.003 (0.002) 1.317 .188 -0.001 0.007 0.026
#> Direct 0.007 (0.007) 0.972 .331 -0.007 0.022 0.070
#> Total 0.032 (0.009) 3.380 <.001 *** 0.013 0.050 0.304
#> ───────────────────────────────────────────────────────────────────────────────
#> Note. Raw (Standard) Confidence Interval (CI) and SE.
#>
# lavaan_summary(lv1, ci="boot", nsim=1000, seed=1)