GRShiny

item_pars <- genIRTpar(nitem = 10, ncat = 3, nfac = 1)

true_theta <- genTheta(nsample = 500, nfac = 1)

grm_dt <- genData(eta = true_theta, ipar = item_pars)

lav_syn <- genLavSyn(dat = grm_dt, nfac = 1)
#> 
#> F1 =~ NA*y1+l1*y1+l2*y2+l3*y3+l4*y4+l5*y5+l6*y6+l7*y7+l8*y8+l9*y9+l10*y10
#> 
#>  
#> F1~~ 1*F1
#> F1~ 0*1  
#> y1 | t11*t1;
#> y2 | t21*t1;
#> y3 | t31*t1;
#> y4 | t41*t1;
#> y5 | t51*t1;
#> y6 | t61*t1;
#> y7 | t71*t1;
#> y8 | t81*t1;
#> y9 | t91*t1;
#> y10 | t101*t1;
#> y1 | t12*t2;
#> y2 | t22*t2;
#> y3 | t32*t2;
#> y4 | t42*t2;
#> y5 | t52*t2;
#> y6 | t62*t2;
#> y7 | t72*t2;
#> y8 | t82*t2;
#> y9 | t92*t2;
#> y10 | t102*t2;

grm.fit <- runGRM(dat = grm_dt, lav.syntax = lav_syn, estimator = "WL")

extract_est(grm.fit)
#>    lhs op rhs label    est    se      z pvalue
#> 1   F1 =~  y1    l1  0.601 0.045 13.232  0.000
#> 2   F1 =~  y2    l2  0.776 0.036 21.647  0.000
#> 3   F1 =~  y3    l3  0.677 0.042 15.954  0.000
#> 4   F1 =~  y4    l4  0.592 0.045 13.201  0.000
#> 5   F1 =~  y5    l5  0.641 0.043 14.774  0.000
#> 6   F1 =~  y6    l6  0.580 0.048 12.183  0.000
#> 7   F1 =~  y7    l7  0.630 0.043 14.797  0.000
#> 8   F1 =~  y8    l8  0.540 0.047 11.615  0.000
#> 9   F1 =~  y9    l9  0.748 0.037 19.942  0.000
#> 10  F1 =~ y10   l10  0.560 0.047 11.892  0.000
#> 11  y1  |  t1   t11 -0.105 0.056 -1.876  0.061
#> 12  y2  |  t1   t21 -0.095 0.056 -1.697  0.090
#> 13  y3  |  t1   t31 -0.075 0.056 -1.340  0.180
#> 14  y4  |  t1   t41 -0.253 0.057 -4.463  0.000
#> 15  y5  |  t1   t51 -0.050 0.056 -0.893  0.372
#> 16  y6  |  t1   t61 -0.025 0.056 -0.447  0.655
#> 17  y7  |  t1   t71 -0.197 0.057 -3.483  0.000
#> 18  y8  |  t1   t81 -0.290 0.057 -5.086  0.000
#> 19  y9  |  t1   t91 -0.197 0.057 -3.483  0.000
#> 20 y10  |  t1  t101 -0.181 0.056 -3.215  0.001
#> 21  y1  |  t2   t12  0.111 0.056  1.965  0.049
#> 22  y2  |  t2   t22  0.111 0.056  1.965  0.049
#> 23  y3  |  t2   t32  0.085 0.056  1.519  0.129
#> 24  y4  |  t2   t42  0.274 0.057  4.819  0.000
#> 25  y5  |  t2   t52  0.243 0.057  4.285  0.000
#> 26  y6  |  t2   t62  0.151 0.056  2.680  0.007
#> 27  y7  |  t2   t72  0.181 0.056  3.215  0.001
#> 28  y8  |  t2   t82  0.207 0.057  3.661  0.000
#> 29  y9  |  t2   t92  0.050 0.056  0.893  0.372
#> 30 y10  |  t2  t102  0.070 0.056  1.251  0.211

ICCplot(grm.fit, 1)

ESplot(grm.fit , 1)

infoPlot(grm.fit, 1)

FSplot(grm.fit)