Based on previous research on conditional reliability for number-correct test scores, conditioned on levels of the logit scale in item response theory, this article deals with conditional reliability of classical-type weighted scores conditioned on latent levels of a bounded scale. This is done in the framework of the D-scoring method of measurement (D-scale, bounded from 0 to 1). Along with the conditional reliability of weighted D-scores, conditioned on latent levels of the D-scale, presented are some additional measures of precision—conditional standard error, conditional signal-to-noise ratio, and marginal reliability. A syntax code (in R) for all computations is also provided.
BrennanR. L. (1998). Misconceptions at the intersection of measurement theory and practice. Educational Measurement: Issues and Practice, 17(1), 5–30.
2.
CronbachL. J.GleserG. C. (1964). The signal/noise ratio in the comparison of reliability coefficients. Educational and Psychological Measurement, 24, 467–480.
3.
DimitrovD. M. (2023). D-scoring method of measurement: Classical and latent frameworks. Routledge.
4.
DimitrovD. M.AlGhamdiH. (2022, September). Piloting of Multistage Testing (MST) under D-scoring method [Conference session]. Paper presented at the 2022 Conference of the International Association of Computer Adaptive Testing (IACAT), Frankfurt, Germany.
5.
DimitrovD. M.SadaawiA. (2024, August). National assessment for schools in Saudi Arabia: Score reliability and plausible values [Conference session]. Paper presented at the 2024 International Conference on Educational Statistics, Evaluation, and Assessment, (ICESEA). Amsterdam, Netherlands.
6.
DimitrovD. M.SadaawiA. (2018). Psychometric features of the general teacher test under the D-scoring model: The case of teacher certification assessment in Saudi Arabia. World Journal of Social Science Research, 5(2), 107–126.
KolenM. J.HansonB. A.BrennanR. L. (1992). Conditional standard errors of measurement for scale scores. Journal of Educational Measurement, 29, 285–307.
9.
LordF. M. (1984). Standard errors of measurement at different ability levels. Journal of Educational Measurement, 21(3), 239–243.
10.
NicewanderW. A. (2018). Conditional reliability coefficients for test scores. Psychological Methods, 23(2), 351–362.
11.
NicewanderW. A. (2019). Conditional precision of measurement for test scores: Are conditional standard errors sufficient?Educational and Psychological Measurement, 79(1), 5–18.
12.
RamsayJ. O.WilbergM. (2017). A strategy for replacing sum scoring. Journal of Educational and Behavioral Statistics, 42(3), 282–307.
13.
RamsayJ. O.WilbergM.LiJ. (2020). Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45(3), 297–315.
14.
RobitzschA. (2021). On the equivalence of the latent D-scoring model and the two-parameter logistic item response theory model. Mathematics. https://doi.org/10.3390/math9131465
15.
SayarA.DimitrovD.SadaawiA. (2024). Standard-setting procedures for the national assessment for schools in Saudi Arabia [Conference session]. Paper presented at the 2024 Annual Meeting of the American Psychological Association (APA), Seatle, WA, United States.
WallmarkJ. (2025, September3–4). IRTorch: Item response theory with Python [Conference session]. Paper presented at the 2025 Frontier Research in Educational Measurement (FREMO) Conference, Oslo, Norway.
18.
WuM. (2004). The role of plausible values in large-scale survey. Studies in Educational Evaluation, 31(2–3), 114–128.
