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Analyze a Latent Heywood Case

A local animal shelter has designed a survey to measure the impact of their Adopt Me program. Viewers rated each dog's picture, background story, and other characteristics to indicate the "adoptableness" of each animal.

The adoptsurvey data contains the six items they rated including pictures, background, loveskids that measure a "good story" latent variable, while energy, wagstail, playful measure an "in person" latent variable. You will build a two-factor model of their survey and examine it for Heywood cases. The lavaan library has been loaded for you.

Diese Übung ist Teil des Kurses

Structural Equation Modeling with lavaan in R

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Anleitung zur Übung

  • The goodstory latent is measured by pictures, background, and loveskids.
  • The inperson latent is measured by energy, wagstail, and playful.
  • Analyze the two-factor model with the cfa() function.

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Look at the data
head(adoptsurvey)

# Build the model
adopt.model <- 'goodstory ___
inperson ___'

# Analyze the model
adopt.fit <- cfa(model = ___, data = ___)
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