Displays the complete classical test theory (CTT) report for an object of
class "summary.ctt" produced by summary.ctt(): the function call, the
full item-level statistics table (including flags, if present), the
test-level reliability summary, and the total-score frequency
distribution, following the sectioned reporting style used by
print.summary.est_irt() in irtQ.
Usage
# S3 method for class 'summary.ctt'
print(x, digits = 3, ...)Arguments
- x
An object of class
"summary.ctt", as returned bysummary.ctt().- digits
Number of decimal places used for display. Default is
3. The values inxare already rounded byctt()(item and test statistics to three decimal places, percentages to two), so a larger value adds no precision.- ...
Additional arguments passed to or from other methods (currently not used).
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)
# print the full report with values rounded to 2 decimal places
print(summary(out), digits = 2)
#>
#> Call:
#> ctt(data = dat)
#>
#> Item-Level Statistics
#> item cats difficulty discrimination_raw discrimination_corrected
#> V1 2 0.89 0.31 0.20
#> V2 2 0.84 0.37 0.25
#> V3 2 0.81 0.48 0.36
#> V4 2 0.76 0.49 0.36
#> V5 2 0.79 0.33 0.20
#> V6 2 0.70 0.40 0.26
#> V7 2 0.64 0.51 0.38
#> V8 2 0.63 0.50 0.36
#> V9 2 0.56 0.38 0.22
#> V10 2 0.50 0.50 0.35
#> V11 2 0.47 0.47 0.32
#> V12 2 0.46 0.46 0.31
#> V13 2 0.41 0.38 0.22
#> V14 2 0.31 0.40 0.25
#> V15 2 0.32 0.39 0.24
#> alpha_removed flag
#> 0.67
#> 0.66
#> 0.65
#> 0.65
#> 0.67
#> 0.66
#> 0.65
#> 0.65
#> 0.67
#> 0.65
#> 0.65
#> 0.66
#> 0.67
#> 0.66
#> 0.67
#>
#> 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 0.68 0.68 1.65 0.6
#> mean_discrimination_raw mean_discrimination_corrected
#> 0.42 0.28
#>
#> 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
#>