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DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Heywood Cases on the Latent Variable Erin Buchanan Professor DataCamp Structural Equation Modeling with lavaan in R Heywood Cases

  1. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Heywood Cases on the Latent Variable Erin Buchanan Professor

  2. DataCamp Structural Equation Modeling with lavaan in R Heywood Cases Correlations that are out of bounds Negative variances

  3. DataCamp Structural Equation Modeling with lavaan in R A Latent Variable Example epi.model <- 'extraversion =~ V3 + V7 + V11 + V15 neuroticism =~ V1 + V5 + V9 + V13 lying =~ V4 + V8 + V12 + V16' epi.fit <- cfa(model = epi.model, data = epi) Warning message: In lav_object_post_check(object) : lavaan WARNING: covariance matrix of latent variables is not positive definite; use inspect(fit,"cov.lv") to investigate.

  4. DataCamp Structural Equation Modeling with lavaan in R How to Fix the Error Warning message: In lav_object_post_check(object) : lavaan WARNING: covariance matrix of latent variables is not positive definite; use inspect(fit,"cov.lv") to investigate. summary(epi.fit, standardized = TRUE, fit.measures = TRUE) Covariances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all extraversion ~~ neuroticism -0.011 0.002 -6.822 0.000 -0.894 -0.894 lying -0.012 0.002 -6.801 0.000 -0.777 -0.777 neuroticism ~~ lying 0.012 0.002 7.023 0.000 0.982 0.982

  5. DataCamp Structural Equation Modeling with lavaan in R How to Fix the Error #original model epi.model <- 'extraversion =~ V3 + V7 + V11 + V15 neuroticism =~ V1 + V5 + V9 + V13 lying =~ V4 + V8 + V12 + V16' #respecify the model epi.model2 <- 'extraversion =~ V3 + V7 + V11 + V15 neuroticism_lie =~ V1 + V5 + V9 + V13 + V4 + V8 + V12 + V16' epi.fit2 <- cfa(model = epi.model2, data = epi) summary(epi.fit2, standardized = T, fit.measures = T) Covariances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all extraversion ~~ neuroticism_li -0.011 0.002 -6.939 0.000 -0.843 -0.843

  6. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Let's practice!

  7. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Heywood Cases on the Manifest Variables Erin Buchanan Professor

  8. DataCamp Structural Equation Modeling with lavaan in R Why Negative Variances? Reasons a negative variance might occur: The model might be misspecified or under identified Smaller sample size or sampling fluctuations Manifest variables have different scales Data is skewed or otherwise non-normal

  9. DataCamp Structural Equation Modeling with lavaan in R Negative Variance Example negative.model <- 'latent1 =~ V1 + V2 + V3 latent2 =~ V4 + V5 + V6' negative.fit <- cfa(negative.model, data = negative_data) Warning message: In lavaan::lavaan(model = negative.model, data = negative_data, : lavaan WARNING: model has NOT converged!

  10. DataCamp Structural Equation Modeling with lavaan in R Negative Variance Example (2) summary(negative.fit, standardized = TRUE, fit.measures = TRUE, rsquare = TRUE) ** WARNING ** lavaan (0.5-23.1097) did NOT converge after 10000 iterations ** WARNING ** Estimates below are most likely unreliable Variances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all .V1 9.990 NA 9.990 0.999 .V2 -3949.334 NA -3949.334 -211.745 .V3 20.620 NA 20.620 1.000 .V4 14.999 NA 14.999 1.000 .V5 11885.910 NA 11885.910 615.668 .V6 11.185 NA 11.185 1.000 latent1 0.006 NA 1.000 1.000 latent2 -0.001 NA NaN NaN

  11. DataCamp Structural Equation Modeling with lavaan in R Negative Variance Example (3) R-Square: Estimate V1 0.001 V2 NA V3 0.000 V4 -0.000 V5 -614.668 V6 -0.000 var(negative_data$V2) [1] 18.83833

  12. DataCamp Structural Equation Modeling with lavaan in R Negative Variance Example (4) negative.model <- 'latent1 =~ V1 + V2 + V3 latent2 =~ V4 + V5 + V6 V2 ~~ 18.83833*V2' negative.fit <- cfa(negative.model, data = negative_data) summary(negative.fit, standardized = TRUE, fit.measures = TRUE, rsquare = TRUE) Variances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all .V2 18.838 18.838 0.962 .V1 7.655 1.145 6.687 0.000 7.655 0.772 .V3 16.100 1.580 10.189 0.000 16.100 0.848 .V4 13.866 1.017 13.638 0.000 13.866 0.876 .V5 8.851 5.472 1.617 0.106 8.851 0.400 .V6 12.336 0.599 20.596 0.000 12.336 0.956 latent1 2.261 1.128 2.004 0.045 1.000 1.000 latent2 1.956 0.875 2.236 0.025 1.000 1.000

  13. DataCamp Structural Equation Modeling with lavaan in R Negative Variance Example (5) R-Square: Estimate V2 0.038 V1 0.228 V3 0.152 V4 0.124 V5 0.600 V6 0.044

  14. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Let's practice!

  15. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Create Diagrams with semPaths() Erin Buchanan Professor

  16. DataCamp Structural Equation Modeling with lavaan in R semPlot and semPaths() #load libraries library(lavaan) library(semPlot) #run your model twofactor.model <- 'text =~ x4 + x5 + x6 speed =~ x7 + x8 + x9' twofactor.fit <- cfa(model = twofactor.model, data = HolzingerSwineford1939) #basic diagram semPaths(object = twofactor.fit)

  17. DataCamp Structural Equation Modeling with lavaan in R semPaths() Default Output

  18. DataCamp Structural Equation Modeling with lavaan in R Editing the Picture semPaths(object = twofactor.fit, whatLabels = "std", edge.label.cex = 1) #whatLabels can also be "par"

  19. DataCamp Structural Equation Modeling with lavaan in R Picture Layout semPaths(object = twofactor.fit, whatLabels = "std", edge.label.cex = 1, layout = "circle") #layout options are tree, circle, spring, tree2, circle2

  20. DataCamp Structural Equation Modeling with lavaan in R Picture Rotation semPaths(object = twofactor.fit, whatLabels = "std", edge.label.cex = 1, layout = "tree", rotation = 2) #layout options are tree, circle, spring, tree2, circle2 #rotation options are 1, 2, 3, 4 for tree layouts

  21. DataCamp Structural Equation Modeling with lavaan in R Color Visualization semPaths(object = twofactor.fit, whatLabels = "std", edge.label.cex = 1, layout = "tree", rotation = 2, what = "std", edge.color = "purple") #what options include par and std

  22. DataCamp Structural Equation Modeling with lavaan in R STRUCTURAL EQUATION MODELING WITH LAVAAN IN R Let's practice!

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