Analyze Text Speed Model
Let's analyze your text speed model from the first lesson. This model included one latent variable, textspeed
, represented by six manifest variables. Variables x4
, x5
, x6
measured reading comprehension, and x7
, x8
, and x9
measured speed counting and addition from the HolzingerSwineford1939
dataset.
We will use the cfa()
function to analyze text.model
using the data from HolzingerSwineford1939
. Our summary should indicate the model was identified with 9 degrees of freedom. You should examine the latent variable estimates to determine which items measure the latent variable well (high scores) and which do not (low scores).
This exercise is part of the course
Structural Equation Modeling with lavaan in R
Exercise instructions
- Use the
cfa()
function to fit a model calledtext.fit
. Remember to include both model and data arguments! - Use the
summary()
function to view the model fit.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load the lavaan library
library(lavaan)
# Load the dataset and define model
data(HolzingerSwineford1939)
text.model <- 'textspeed =~ x4 + x5 + x6 + x7 + x8 + x9'
# Analyze the model with cfa()
# Summarize the model