#import data into RStudio
library(haven) 
UETALQ_survey_data <- read_sav("C:/Users/gbro008/Google Drive/1995 to 2025 All PUBS/Teachers/working folders/2017 Xu & Brown TALQ/UETALQ-survey-data.sav")
View(UETALQ_survey_data)

#lavaan code UETALQ 24 item dichotomous test analysis
#create model
TALQ.model <- 'TALQ =~ q1 +q2 + q3 +q4 +q5 + q6 + q7 + q8 + q9 + q10 + q11 + q12 + q13 + q14 + q15 + q16 + q17 + q18 + q19 + q20 + q21 + q22 + q23 + q24'

#cfa analysis with WLS=ADF estimator, ordered command to inform CFA that this is ordered scores
TALQ_fit <-cfa (TALQ.model, data=UETALQ_survey_data, ordered=c("q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9", "q10", "q11", "q12", "q13", "q14", "q15", "q16", "q17", "q18", "q19", "q20", "q21", "q22", "q23", "q24"), estimator="wls")

#standard output of fit and values
summary(TALQ_fit, standardized=TRUE)
#detailed fit indices
fitmeasures(TALQ_fit)

#to get gamma hat fit index
library(semTools)
moreFitIndices(TALQ_fit)

#to get x2/df ratio and p-value-thanks to Terry Jorgensen UvA (amsterdam)
fm <- fitMeasures(TALQ_fit)
fm[["chisq"]] / fm[["df"]]
fm["pvalue"] 
#get a picture,standardised scores shown
library(lavaanPlot)
lavaanPlot(model = TALQ_fit, node_options = list(shape = "box", fontname = "Helvetica"), edge_options = list(color = "grey"), coefs = TRUE, stand=TRUE)