We are conducting a study in educational science where raters are assessing teachers.
The data structure is fully cross-classified, meaning that all raters are rating all teachers. In our case all 8 raters are rating the same 46 teachers with the same items. All teachers are rated by all raters.
We would like to conduct a multilevel CFA where the teachers are at level 2 and the raters are at level 1.
This is the syntax (using the cfa function from the lavaan package)
model <- "level:1 f1 =~ item1 + a*item2 + b*item3 + c*item4 + (1|rater) f2 =~ item5 + d*item6 + e*item7 + (1|rater) level:2 f1 =~ item1 + a*item2 + b*item3 + c*item4 f2 =~ item5 + d*item6 + e*item7 item2 ~~ 0*item2 item5 ~~ 0*item5 item6 ~~ 0*item6 item7 ~~ 0*item7" multilevel_cfa <-cfa(model, data=dat, std.lv = FALSE, verbose= FALSE, cluster = "teacher")
We would like to conduct a fully cross classified multilevel CFA. The rater (1|rater) are the identifiers for the videos.
- Is the syntax correct?
- At first we got negative variance. Then the variances for the items in question were fixed to zero. Is this approach (fixing variances to zero) acceptable?
datatable_screenshot.pdf (221.8 KB)