library(haven)
library(ltm)
library(dplyr)
df <- haven::read_sav("/students/aamenshikova/Kaluga/IRT Summer/base_ko.sav")
School Connectedness
s_con <- dplyr::select(df,sc1,sc2,sc3,sc4,sc5,sc6,sc7,sc8,sc9)
mdl1 <- grm(s_con, constrained = FALSE, na.action = na.exclude)
mdl1
##
## Call:
## grm(data = s_con, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## sc1 -1.966 -1.058 0.343 3.147
## sc2 -2.274 -1.530 -0.150 2.492
## sc3 -2.313 -1.211 0.372 1.848
## sc4 -1.509 -0.239 1.180 1.958
## sc5 -2.957 -1.657 0.397 1.548
## sc6 -2.541 -1.088 0.641 1.287
## sc7 -2.923 -1.675 -0.237 1.231
## sc8 -3.668 -2.062 0.036 1.043
## sc9 -2.604 -1.122 0.957 1.624
##
## Log.Lik: -245895.8
Engagement
eng <- dplyr::select(df,e1,e2,e3,e4,e5,e6,e7,e8)
mdl2 <- grm(eng, constrained = FALSE, na.action = na.exclude)
mdl2
##
## Call:
## grm(data = eng, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## e1 -2.719 -1.560 0.403 1.603
## e2 -5.481 -2.858 1.855 0.467
## e3 -3.219 -0.854 1.436 0.824
## e4 -3.509 -1.990 0.315 0.856
## e5 -3.399 -1.923 0.153 0.955
## e6 -2.403 -1.456 -0.062 1.953
## e7 -2.041 -0.967 0.440 1.751
## e8 -2.120 -1.513 -0.294 2.708
##
## Log.Lik: -235989.8
Aggressiveness
agr <- dplyr::select(df,agres1,agres2,agres3,agres4)
mdl3 <- ltm::grm(agr, constrained = FALSE,start.val = "random", na.action = na.exclude)
Teacher Effectiveness
te <- dplyr::select(df,te1,te2,te3)
mdl4 <- ltm::grm(te, constrained = FALSE, na.action = na.exclude)
mdl4
##
## Call:
## ltm::grm(data = te, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## te1 -2.193 -1.261 -0.004 2.881
## te2 -2.406 -1.579 -0.114 3.070
## te3 -2.314 -1.281 0.147 2.661
##
## Log.Lik: -72764.35
Teacher Relations
tr <- dplyr::select(df,tr1,tr2,tr3,tr4)
mdl5 <- ltm::grm(tr, constrained = FALSE, na.action = na.exclude)
mdl5
##
## Call:
## ltm::grm(data = tr, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## tr1 -2.505 -1.417 0.102 1.872
## tr2 -2.868 -1.648 -0.074 1.653
## tr3 -2.074 -1.187 0.180 3.864
## tr4 -2.086 -1.178 0.182 3.352
##
## Log.Lik: -100006.1
Self-Esteem Math
sem <- dplyr::select(df,seM1,seM2,seM3,seM4)
mdl6 <- ltm::grm(sem, constrained = FALSE, na.action = na.exclude,start.val = "random")
mdl6
##
## Call:
## ltm::grm(data = sem, constrained = FALSE, start.val = "random",
## na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## seM1 1.464 0.259 -0.900 -2.917
## seM2 1.550 0.475 -0.749 -2.621
## seM3 2.055 0.804 -0.581 -1.128
## seM4 2.110 1.028 -0.322 -1.918
##
## Log.Lik: -126972.3
Self-Esteem Human
seh <- dplyr::select(df,seH1,seH2,seH3,seH4)
mdl7 <- ltm::grm(seh, constrained = FALSE,start.val = "random", na.action = na.exclude)
mdl7
##
## Call:
## ltm::grm(data = seh, constrained = FALSE, start.val = "random",
## na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## seH1 -2.163 -0.778 0.787 2.337
## seH2 -3.547 -2.042 -0.202 1.300
## seH3 -2.567 -1.047 0.769 0.965
## seH4 -2.130 -0.625 1.066 1.708
##
## Log.Lik: -122771.9
Bulling
bul <- dplyr::select(df,bul1,bul2,bul3,bul4, bul5, bul6, bul7, bul8, bul9, bul10)
mdl8 <- ltm::grm(bul, constrained = FALSE, na.action = na.exclude)
mdl8
##
## Call:
## ltm::grm(data = bul, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## bul1 0.804 1.745 2.383 3.260
## bul2 0.095 1.401 2.211 2.671
## bul3 0.265 1.549 2.468 1.835
## bul4 1.199 2.828 3.808 1.318
## bul5 1.490 2.547 3.166 2.164
## bul6 0.368 1.736 2.573 2.300
## bul7 0.100 1.625 2.606 1.703
## bul8 0.591 2.705 3.768 1.120
## bul9 1.045 2.257 2.996 1.840
## bul10 0.502 1.738 2.526 2.240
##
## Log.Lik: -192801.2
Cyberbulling
cyb <- dplyr::select(df,cyb1,cyb2,cyb3)
mdl9 <- ltm::grm(cyb, constrained = FALSE, na.action = na.exclude)
mdl9
##
## Call:
## ltm::grm(data = cyb, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Extrmt4 Dscrmn
## cyb1 0.261 1.131 1.931 2.820 2.208
## cyb2 1.029 1.794 2.466 3.132 2.415
## cyb3 0.604 1.312 1.942 2.707 3.480
##
## Log.Lik: -65765.74
School Conditions?
sccond <- dplyr::select(df,sc_cond1,sc_cond2,sc_cond3,sc_cond4,sc_cond5,sc_cond6)
mdl10 <- ltm::grm(sccond, constrained = FALSE, na.action = na.exclude)
mdl10
##
## Call:
## ltm::grm(data = sccond, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## sc_cond1 -1.746 -0.354 1.246 1.243
## sc_cond2 -1.217 0.058 1.358 1.943
## sc_cond3 -0.959 0.720 2.007 2.031
## sc_cond4 -0.699 0.866 2.042 2.026
## sc_cond5 -1.166 0.121 1.343 2.666
## sc_cond6 -0.710 1.449 3.376 1.116
##
## Log.Lik: -185952.6
Relationship
relat <- dplyr::select(df,rel1,rel2,rel3,rel4)
mdl11 <- ltm::grm(relat, constrained = FALSE, na.action = na.exclude)
mdl11
##
## Call:
## ltm::grm(data = relat, constrained = FALSE, na.action = na.exclude)
##
## Coefficients:
## Extrmt1 Extrmt2 Extrmt3 Dscrmn
## rel1 -2.757 -1.866 -0.393 1.897
## rel2 -2.498 -1.270 0.677 1.834
## rel3 -2.194 -1.223 -0.040 2.234
## rel4 -2.939 -1.275 0.621 1.041
##
## Log.Lik: -112301.5