A restricted latent class model with polytomous attributes and respondent-level covariates

Wayman, Eric Alan; Culpepper, Steven Andrew; Douglas, Jeff; Bowers, Jesse

doi:10.1007/s41237-025-00271-8

Table 2 Results of first simulation study (contd.)

From: A restricted latent class model with polytomous attributes and respondent-level covariates

\(N\)	\(J\)	\(K\)	\(L\)	\(\rho\)	\(\beta\)	\(\delta\)	\(\delta ^0\)	\(\delta ^1\)	\(\beta ^0\)	\(\beta^1\)
500	15	2	2	0.000	0.093	0.974	0.921	1.000	0.037	0.121
500	15	2	3	0.000	0.190	0.962	0.932	0.986	0.076	0.282
500	25	3	2	0.000	0.069	0.987	0.979	1.000	0.024	0.136
500	25	3	3	0.000	0.103	0.970	0.985	0.932	0.030	0.285
500	45	4	2	0.000	0.060	0.988	0.985	0.995	0.021	0.160
500	15	2	2	0.250	0.095	0.969	0.908	1.000	0.041	0.122
500	15	2	3	0.250	0.155	0.989	0.983	0.994	0.024	0.259
500	25	3	2	0.250	0.067	0.988	0.980	0.999	0.025	0.131
500	25	3	3	0.250	0.158	0.945	0.956	0.917	0.070	0.380
500	45	4	2	0.250	0.050	0.993	0.991	0.998	0.015	0.137
500	15	2	2	0.500	0.099	0.969	0.908	1.000	0.042	0.128
500	15	2	3	0.500	0.143	0.980	0.962	0.994	0.038	0.227
500	25	3	2	0.500	0.198	0.906	0.856	0.982	0.172	0.237
500	25	3	3	0.500	0.282	0.873	0.862	0.900	0.189	0.515
500	45	4	2	0.500	0.117	0.952	0.943	0.973	0.071	0.234
1500	15	2	2	0.000	0.053	0.988	0.964	1.000	0.015	0.072
1500	15	2	3	0.000	0.139	0.977	0.967	0.986	0.040	0.218
1500	25	3	2	0.000	0.036	0.994	0.990	1.000	0.009	0.076
1500	25	3	3	0.000	0.069	0.980	0.990	0.956	0.016	0.202
1500	45	4	2	0.000	0.041	0.987	0.983	0.997	0.018	0.097
1500	15	2	2	0.250	0.051	0.990	0.969	1.000	0.016	0.069
1500	15	2	3	0.250	0.115	0.991	0.992	0.990	0.010	0.199
1500	25	3	2	0.250	0.033	0.995	0.992	1.000	0.008	0.071
1500	25	3	3	0.250	0.120	0.955	0.963	0.936	0.052	0.293
1500	45	4	2	0.250	0.026	0.997	0.995	1.000	0.007	0.076
1500	15	2	2	0.500	0.053	0.991	0.972	1.000	0.017	0.070
1500	15	2	3	0.500	0.101	0.987	0.982	0.991	0.016	0.168
1500	25	3	2	0.500	0.143	0.931	0.899	0.979	0.120	0.176
1500	25	3	3	0.500	0.257	0.866	0.848	0.911	0.188	0.433
1500	45	4	2	0.500	0.089	0.956	0.945	0.982	0.057	0.171
3000	15	2	2	0.000	0.035	0.996	0.987	1.000	0.007	0.049
3000	15	2	3	0.000	0.156	0.971	0.963	0.978	0.056	0.235
3000	25	3	2	0.000	0.023	0.997	0.995	1.000	0.004	0.052
3000	25	3	3	0.000	0.052	0.985	0.993	0.965	0.009	0.159
3000	45	4	2	0.000	0.033	0.988	0.985	0.996	0.015	0.077
3000	15	2	2	0.250	0.035	0.993	0.979	1.000	0.009	0.047
3000	15	2	3	0.250	0.102	0.990	0.993	0.988	0.006	0.179
3000	25	3	2	0.250	0.025	0.996	0.993	1.000	0.007	0.053
3000	25	3	3	0.250	0.112	0.955	0.961	0.939	0.048	0.276
3000	45	4	2	0.250	0.020	0.995	0.994	0.998	0.006	0.058
3000	15	2	2	0.500	0.037	0.992	0.977	1.000	0.010	0.051
3000	15	2	3	0.500	0.086	0.988	0.988	0.988	0.009	0.148
3000	25	3	2	0.500	0.167	0.905	0.861	0.972	0.156	0.183
3000	25	3	3	0.500	0.199	0.895	0.877	0.940	0.147	0.328
3000	45	4	2	0.500	0.057	0.971	0.965	0.988	0.033	0.119

Values displayed for \(\beta\) parameters are the average, taken over all elements of the parameter, of the mean absolute error of estimation of each element over all replications. Values displayed for \(\delta\) parameters are the average, taken over all elements of the parameter, of the recovery accuracy of each element over all replications

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