Prepares the full, detailed report for an object of class "ctt"
returned by ctt(). Following the convention used by
est_irt()/summary.est_irt(), this method returns an object of
class "summary.ctt" whose own print.summary.ctt() method displays the
complete item-level table, test-level reliability summary, and total-score
frequency distribution.
Usage
# S3 method for class 'ctt'
summary(object, ...)Arguments
- object
An object of class
"ctt", as returned byctt().- ...
Additional arguments passed to or from other methods (currently not used).
Value
An object of class "summary.ctt": a list with the same item,
crit, alpha, freq, and call elements as object (see
ctt()'s Value), to be displayed by print.summary.ctt().
Author
Hwanggyu Lim hglim83@gmail.com
Examples
# simulate the responses of 300 examinees to 15 dichotomous 3PLM items
set.seed(1)
x <- shape_df(
par.drm = list(a = rep(1.5, 15), b = seq(-1.5, 1.5, length.out = 15),
g = rep(0.2, 15)),
cats = 2, model = "3PLM"
)
dat <- simdat(x = x, theta = rnorm(300), D = 1)
# run the CTT analysis
out <- ctt(data = dat)
# create the full report object and print it
summary(out)
#>
#> Call:
#> ctt(data = dat)
#>
#> Item-Level Statistics
#> item cats difficulty discrimination_raw discrimination_corrected
#> V1 2 0.887 0.309 0.205
#> V2 2 0.837 0.369 0.250
#> V3 2 0.813 0.479 0.365
#> V4 2 0.763 0.489 0.364
#> V5 2 0.790 0.329 0.195
#> V6 2 0.697 0.403 0.257
#> V7 2 0.637 0.514 0.375
#> V8 2 0.630 0.498 0.356
#> V9 2 0.560 0.376 0.215
#> V10 2 0.500 0.497 0.349
#> V11 2 0.467 0.470 0.319
#> V12 2 0.457 0.459 0.307
#> V13 2 0.407 0.382 0.223
#> V14 2 0.313 0.395 0.247
#> V15 2 0.323 0.386 0.236
#> alpha_removed flag
#> 0.668
#> 0.664
#> 0.651
#> 0.649
#> 0.670
#> 0.663
#> 0.646
#> 0.649
#> 0.669
#> 0.650
#> 0.654
#> 0.656
#> 0.668
#> 0.664
#> 0.666
#>
#> Flagging thresholds: difficulty in [0.1, 0.95], discrimination >= 0.2 (raw item-total correlation)
#> 0 of 15 item(s) flagged.
#>
#> Test-Level Reliability Summary
#> n_examinee n_item alpha alpha_std sem mean_difficulty
#> 300 15 0.675 0.675 1.648 0.605
#> mean_discrimination_raw mean_discrimination_corrected
#> 0.424 0.284
#>
#> Total-Score Frequency Distribution
#> score freq pct cum_pct
#> 3 6 2.00 2.00
#> 4 16 5.33 7.33
#> 5 16 5.33 12.67
#> 6 24 8.00 20.67
#> 7 32 10.67 31.33
#> 8 27 9.00 40.33
#> 9 37 12.33 52.67
#> 10 42 14.00 66.67
#> 11 38 12.67 79.33
#> 12 23 7.67 87.00
#> 13 22 7.33 94.33
#> 14 10 3.33 97.67
#> 15 7 2.33 100.00
#>