Dakle Skala stava o tjelesnom kažnjavanju - 9 čestica. CFI, TLI, SRMR ok, RMSEA nije i ne znam zašto…
Vidi saturacije kak su lijepe :), fakat je jasna priča i PCA kaže 72% varijance objašnjeno
library(tidyverse)
library(lavaan)
baza=sjlabelled::read_spss("data/baza.sav")
model='
att_cp =~ SSSTK1 + SSSTK2 + SSSTK3 + SSSTK4 + SSSTK5 + SSSTK6 + SSSTK7 + SSSTK8 + SSSTK9
'
fit=cfa(model= model, data=baza, estimator="ML")
knitr::kable(fitmeasures(fit, fit.measures = c("chisq", "df", "pvalue", "cfi", "tli", "rmsea", "srmr" )))
| chisq |
291.2951826 |
| df |
27.0000000 |
| pvalue |
0.0000000 |
| cfi |
0.9625316 |
| tli |
0.9500422 |
| rmsea |
0.1065637 |
| srmr |
0.0302977 |
knitr::kable(parameterestimates(fit, standardized=T))
| att_cp |
=~ |
SSSTK1 |
1.0000000 |
0.0000000 |
NA |
NA |
1.0000000 |
1.0000000 |
1.2824467 |
0.8745054 |
0.8745054 |
| att_cp |
=~ |
SSSTK2 |
1.0023468 |
0.0285553 |
35.10201 |
0 |
0.9463795 |
1.0583141 |
1.2854563 |
0.8592434 |
0.8592434 |
| att_cp |
=~ |
SSSTK3 |
1.0604706 |
0.0274677 |
38.60789 |
0 |
1.0066348 |
1.1143063 |
1.3599969 |
0.8990098 |
0.8990098 |
| att_cp |
=~ |
SSSTK4 |
1.0282832 |
0.0295088 |
34.84671 |
0 |
0.9704471 |
1.0861193 |
1.3187184 |
0.8561169 |
0.8561169 |
| att_cp |
=~ |
SSSTK5 |
-0.8091070 |
0.0285243 |
-28.36558 |
0 |
-0.8650135 |
-0.7532005 |
-1.0376366 |
-0.7643168 |
-0.7643168 |
| att_cp |
=~ |
SSSTK6 |
-0.6659470 |
0.0265285 |
-25.10310 |
0 |
-0.7179419 |
-0.6139521 |
-0.8540415 |
-0.7077238 |
-0.7077238 |
| att_cp |
=~ |
SSSTK7 |
-0.9842795 |
0.0272125 |
-36.17010 |
0 |
-1.0376151 |
-0.9309440 |
-1.2622860 |
-0.8719681 |
-0.8719681 |
| att_cp |
=~ |
SSSTK8 |
0.9703914 |
0.0253707 |
38.24855 |
0 |
0.9206658 |
1.0201170 |
1.2444752 |
0.8951872 |
0.8951872 |
| att_cp |
=~ |
SSSTK9 |
-0.7116721 |
0.0278872 |
-25.51971 |
0 |
-0.7663299 |
-0.6570143 |
-0.9126815 |
-0.7153828 |
-0.7153828 |
| SSSTK1 |
~~ |
SSSTK1 |
0.5059006 |
0.0282934 |
17.88051 |
0 |
0.4504465 |
0.5613547 |
0.5059006 |
0.2352402 |
0.2352402 |
| SSSTK2 |
~~ |
SSSTK2 |
0.5857163 |
0.0320686 |
18.26449 |
0 |
0.5228630 |
0.6485695 |
0.5857163 |
0.2617008 |
0.2617008 |
| SSSTK3 |
~~ |
SSSTK3 |
0.4388879 |
0.0257876 |
17.01935 |
0 |
0.3883452 |
0.4894306 |
0.4388879 |
0.1917814 |
0.1917814 |
| SSSTK4 |
~~ |
SSSTK4 |
0.6336556 |
0.0345637 |
18.33298 |
0 |
0.5659120 |
0.7013992 |
0.6336556 |
0.2670639 |
0.2670639 |
| SSSTK5 |
~~ |
SSSTK5 |
0.7663886 |
0.0392545 |
19.52357 |
0 |
0.6894511 |
0.8433261 |
0.7663886 |
0.4158199 |
0.4158199 |
| SSSTK6 |
~~ |
SSSTK6 |
0.7268442 |
0.0365648 |
19.87824 |
0 |
0.6551785 |
0.7985100 |
0.7268442 |
0.4991270 |
0.4991270 |
| SSSTK7 |
~~ |
SSSTK7 |
0.5022626 |
0.0279800 |
17.95076 |
0 |
0.4474227 |
0.5571024 |
0.5022626 |
0.2396716 |
0.2396716 |
| SSSTK8 |
~~ |
SSSTK8 |
0.3838940 |
0.0223452 |
17.18015 |
0 |
0.3400982 |
0.4276898 |
0.3838940 |
0.1986399 |
0.1986399 |
| SSSTK9 |
~~ |
SSSTK9 |
0.7946644 |
0.0400561 |
19.83877 |
0 |
0.7161558 |
0.8731730 |
0.7946644 |
0.4882275 |
0.4882275 |
| att_cp |
~~ |
att_cp |
1.6446694 |
0.1017036 |
16.17120 |
0 |
1.4453340 |
1.8440049 |
1.0000000 |
1.0000000 |
1.0000000 |
Korelacije
Nemam pojma jel u ovome problem, iako je to razumno za jednofaktorsku skalu
b2=baza %>% select(SSSTK1, SSSTK2, SSSTK3, SSSTK4, SSSTK5, SSSTK6, SSSTK7, SSSTK8, SSSTK9)
rajter.flex::cor.flex(b2)$matrix
Br. | Varijabla | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
1 | SSSTK1 | 1.000 |
|
|
|
|
|
|
|
2 | SSSTK2 | 0.720*** | 1.000 |
|
|
|
|
|
|
3 | SSSTK3 | 0.802*** | 0.796*** | 1.000 |
|
|
|
|
|
4 | SSSTK4 | 0.793*** | 0.726*** | 0.764*** | 1.000 |
|
|
|
|
5 | SSSTK5 | -0.700*** | -0.628*** | -0.651*** | -0.684*** | 1.000 |
|
|
|
6 | SSSTK6 | -0.564*** | -0.614*** | -0.630*** | -0.566*** | 0.544*** | 1.000 |
|
|
7 | SSSTK7 | -0.761*** | -0.730*** | -0.773*** | -0.739*** | 0.691*** | 0.648*** | 1.000 |
|
8 | SSSTK8 | 0.776*** | 0.808*** | 0.787*** | 0.768*** | -0.679*** | -0.642*** | -0.784*** | 1.000 |
9 | SSSTK9 | -0.587*** | -0.598*** | -0.693*** | -0.558*** | 0.533*** | 0.632*** | 0.651*** | -0.615*** |