Exercise

Exploring factor scores

Factor scores represent individual respondents' standing on a latent factor. While not used for scale validation per se, factor scores can be used for customer segmentation via clustering, network analysis and other statistical techniques. Let's explore the factor scores of the brand_rep_cfa model.

lavaan, psych and purrr have been loaded into your environment.

Instructions

100 XP

Compute the factor scores in lavaan, storing the output as a data frame, brand_rep_scores.
Get descriptive statistics of our factor scores using the relevant psych function.
Plot a histogram for each variable in brand_repscores.
Is each factor score normally distributed? Check using map() from purrr in conjunction with shapiro.test() for univariate normality.

Take Hint (-30 XP)