R Notebook

Load Libraries

library(foreign)
library(tidyLPA)
library(dplyr)

Load Data

data <- read.spss("data.sav", to.data.frame = T)

data.sav: Very long string record(s) found (record type 7, subtype 14), each will be imported in consecutive separate variables

Find Best Fitting Model

It appears as though model 2 with 2 profiles fits best (as indicated by low BIC). Model 3 with 3 profiles has the lowest BIC but I’m suspicious of it due to large variance.

Model 2 with 2 Profiles

model2 <- estimate_profiles(data, 
                        RTA_factor_1, RTA_factor_2, RTA_factor_3, RTA_factor_4,
                        model = 2,
                        n_profiles = 2) 

Fit varying means, equal variances and covariances (Model 2) model with 2 profiles.
LogLik is 5493.057
BIC is 11094.924
Entropy is 0.925

Entropy is above .8 suggesting distinct profiles.

Estimated Means and Variance for Model 2

y-axis = mean

y-axis = mean centered

y-axis = standard deviation

Model 3 with 3 Profiles

model3 <- estimate_profiles(data, 
                        RTA_factor_1, RTA_factor_2, RTA_factor_3, RTA_factor_4,
                        model = 3,
                        n_profiles = 3) 

Fit varying means and variances, covariances fixed to 0 (Model 3) model with 3 profiles.
LogLik is 5403.342
BIC is 10955.582
Entropy is 0.928

y-axis = mean

y-axis = mean centered

y-axis = standard deviation