How can I plot standardized loadings (Std.all) in a CFA analysis with R instead of raw estimates? Try this alternative approach:
library(cfaVizR)
# Generate synthetic data
sampleData <- data.frame(a = rnorm(15), b = rnorm(15), c = rnorm(15))
# Specify the CFA model
modelDef <- 'factor1 =~ a + b + c'
# Run the CFA
cfaResult <- executeCFA(modelDef, sampleData)
# Plot using standardized loadings
displayCFA(cfaResult, showStd = TRUE)
hey, try using semPaths from semPlot package to display std. loadings. it’s a slick way to see model strcture without raw clutter. might be a cool alt to explore!
Hey everyone, I’ve been tinkering with some alternatives and wanted to share my little adventure with the qgraph package for visualizing standardized loadings. I fitted my CFA using lavaan, snagged the Std.all estimates with standardizedSolution(), and then fed those values into qgraph. What really struck me was how naturally it displays the underlying structure in a more network-like way – it’s almost like watching the model come to life!
I’m curious, has anyone else’s experience with qgraph been similar? Or maybe you’ve found other neat interactive approaches that let you dive deep into details while keeping the visualization intuitive? Would love to hear your thoughts or any cool customizations you’ve tried out. Cheers and happy modeling! 
Hey everyone! I’ve been exploring how to showcase standardized loadings in CFA models and stumbled on something neat with the tidySEM package. I converted my model results into a tidy format, which made it super simple to plot the standardized estimates using ggplot2. What I really like is the extra control over aesthetics — you can tweak labels, colors, and even add annotations to highlight key parts of your model. I find this approach especially handy if you want a bit more flair than the default plots. Has anyone else experimented with tidySEM or maybe merged it with custom ggplot tweaks? I’m curious to hear if there are any cool tips or variations others are using. Cheers and happy modeling!
Based on my experiences, I found a neat workaround using the lavaan package to extract standardized loadings and then manually creating a custom plot with ggplot2. Essentially, after fitting your model you’ll use standardizedSolution() to get the Std.all estimates and then restructure that output for plotting. This approach allows you to adjust labels, lines, and other aesthetics to really tailor the visualization to your needs. Although it requires a bit more code than some out‐of‐the‐box solutions, I appreciate the flexibility it offers, especially when dealing with complex models.
hey all, i’ve had luck using networkD3 to build interctive graphs of std loadings from lavaan. easy drag-n-drop node plots can show model flow, and it’s a fun, dynamic viz alternative. hope this helps!