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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).

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Structural Equation Modeling with lavaan in R

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Instrucciones del ejercicio

  • Use the cfa() function to fit a model called text.fit. Remember to include both model and data arguments!
  • Use the summary() function to view the model fit.

Ejercicio interactivo práctico

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# 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
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