Print Summary of IRT Simulation Results
Source:R/summary_irt_results.R
print.summary_irt_results.RdDisplay item parameter criteria and theta recovery statistics from a
summary.irt_results() object.
Usage
# S3 method for class 'summary_irt_results'
print(x, ...)Examples
# \donttest{
design <- irt_design(
model = "1PL", n_items = 5,
item_params = list(b = seq(-2, 2, length.out = 5))
)
study <- irt_study(design, sample_sizes = c(200, 500))
results <- irt_simulate(study, iterations = 10, seed = 42)
#> Iteration 4/10
#> Iteration 5/10
#> Iteration 7/10
#> Iteration 8/10
#> Iteration 9/10
#> Iteration 10/10
#>
s <- summary(results)
print(s)
#> IRT Simulation Summary
#> Model: 1PL
#> Iterations: 10
#> Seed: 42
#>
#> Item Parameter Criteria:
#> sample_size item param true_value bias empirical_se mse
#> 200 1 b -2 0.01826936 0.2813439 0.07157270
#> 200 2 b -1 -0.05712048 0.2314278 0.05146568
#> 200 3 b 0 -0.07594365 0.2225141 0.05032873
#> 200 4 b 1 -0.03849063 0.1497202 0.02165607
#> 200 5 b 2 0.05270597 0.3076836 0.08798018
#> 500 1 b -2 0.02029278 0.1618503 0.02398776
#> 500 2 b -1 0.04266708 0.1450726 0.02076192
#> 500 3 b 0 -0.04696731 0.1306269 0.01756299
#> 500 4 b 1 0.08968595 0.1061969 0.01819357
#> 500 5 b 2 -0.03168185 0.1287219 0.01591614
#> rmse coverage mcse_bias mcse_mse n_converged
#> 0.2675307 0.9 0.08896874 0.037426556 10
#> 0.2268605 0.8 0.07318389 0.019402165 10
#> 0.2243407 0.8 0.07036515 0.025615834 10
#> 0.1471600 1.0 0.04734570 0.005954864 10
#> 0.2966145 0.9 0.09729809 0.074831545 10
#> 0.1548798 0.8 0.05118155 0.010034577 10
#> 0.1440900 0.9 0.04587597 0.006047372 10
#> 0.1325254 1.0 0.04130787 0.004460940 10
#> 0.1348835 1.0 0.03358240 0.005734851 10
#> 0.1261592 1.0 0.04070544 0.005735466 10
#>
#> Theta Recovery:
#> sample_size mean_cor sd_cor mean_rmse sd_rmse n_converged
#> 200 0.6710695 0.05118505 0.7312415 0.05366362 10
#> 500 0.6533689 0.02817120 0.7587360 0.02548581 10
# }