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Analyze a Manifest Heywood Case

After reporting your findings, the adoption group recreated their survey to measure two factors: how effective their online story posts were in goodstory and how much an inperson interaction mattered. The new data is loaded under adoptsurvey. In this exercise, you will look for a Heywood cases on one of the manifest variables, rather than on the latent variable.

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100 XP

Analyze the updated data adoptsurvey for the two factor adopt.model with the cfa() function.
Watch for warnings after the cfa() has been analyzed.
Use the summary() function to explore which manifest variable is problematic.

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