Research Article

The Effects of Reusing Written Test Items: A Study Using the Rasch Model

Table 3

Psychometric results.

Item difficulty (classical test theory)Item difficulty and fit statistics (Rasch model)
Number of persons per analysis

Test 1–Test 4
basic analysis  
First use/reuse analysis  
Test 1 
Test 2 
Test 3 
Test 4 
Number of items per analysis

191414153333 + 15 + 2 = 50 items
Easiness (s.e.)
I.Nb.ppppEasinessOutfitInfit1st use2nd use3rd use

Published items
10.990.980.940.971.660.680.861.86 (0.28)
190.790.790.850.25−1.631.071.04−1.49 (0.12)
230.960.950.910.880.561.020.940.75 (0.18)
370.860.850.810.940.020.890.960.21 (0.16)
New in test 1
50.90−0.110.800.97−0.25 (0.36)
70.910.011.130.96−0.13 (0.38)
250.870.76−0.711.000.96−0.55 (0.33)−1.05 (0.36)
270.981.600.520.881.46 (0.72)
310.890.91−0.110.610.81−0.35 (0.35)−0.01 (0.29)
320.920.141.160.960.00 (0.39)
330.940.990.950.761.000.32 (0.44)2.28 (0.58)
400.920.87−0.050.960.970.00 (0.39)−0.24 (0.42)
410.820.78−0.981.031.02−0.87 (0.31)−1.07 (0.23)
430.78−1.011.111.01−1.14 (0.29)
440.720.75−1.350.940.96−1.49 (0.27)−1.24 (0.22)
450.400.450.40−2.741.021.02−2.95 (0.27)−2.66 (0.21)−2.73 (0.32)
470.940.971.630.730.880.32 (0.44)2.90 (0.59)
480.650.64−1.211.051.07−1.84 (0.26)−0.60 (0.20)
490.980.980.961.880.710.891.46 (0.72)1.56 (0.52)2.61 (0.51)
New in test 2
20.992.970.290.842.98 (1.00)
60.900.930.030.860.96−0.08 (0.29)0.50 (0.52)
80.86−0.550.910.92−0.52 (0.26)
300.870.62−0.800.820.91−0.37 (0.27)−0.65 (0.25)
340.650.60−1.471.081.06−1.78 (0.21)−0.79 (0.20)
New in test 3
40.910.220.510.720.28 (0.48)
150.850.981.301.130.90−0.38 (41)3.32 (0.71)
290.76−1.101.011.03−1.05 (0.36)
360.940.70−0.490.870.930.76 (0.56)−0.30 (0.21)
500.930.440.960.780.50 (0.52)
New in test 4
30.820.150.820.930.53 (0.24)
90.840.290.730.900.67 (0.25)
100.820.150.880.930.53 (0.24)
420.870.340.750.910.72 (0.25)

I.Nb. = Item number; = item difficulty (classical test theory); easiness = relative item difficulty (probabilistic psychometric analysis); higher values indicate easier items; s.e. = standard error; outfit/infit = fit statistics (indicating the degree of fit with the Rasch model); values around +1 are regarded as indicating a fit with the Rasch model; values close to 0 indicate an overfit (less variation than expected); values exceeding 1 indicate an underfit (more variation than expected).