Generalized network structured models with mixed responses subject to measurement error and misclassification

Biometrics ◽  
2022 ◽  
Author(s):  
Qihuang Zhang ◽  
Grace Y. Yi
Keyword(s):  
Measurement Error ◽  
Mixed Responses

Benefits from Computerized Adaptive Testing as Seen in Simulation Studies

1999 ◽  
Vol 15 (2) ◽  
pp. 91-98 ◽  
Author(s):  
Lutz F. Hornke
Keyword(s):  
Measurement Error ◽  
Computerized Adaptive Testing ◽  
Test Procedure ◽  
Adaptive Testing ◽  
Parameter Estimates ◽  
Simulation Studies ◽  
Computerized Adaptive Test ◽  
Item Banks ◽  
Item Parameters ◽  
General Reliability

Summary: Item parameters for several hundreds of items were estimated based on empirical data from several thousands of subjects. The logistic one-parameter (1PL) and two-parameter (2PL) model estimates were evaluated. However, model fit showed that only a subset of items complied sufficiently, so that the remaining ones were assembled in well-fitting item banks. In several simulation studies 5000 simulated responses were generated in accordance with a computerized adaptive test procedure along with person parameters. A general reliability of .80 or a standard error of measurement of .44 was used as a stopping rule to end CAT testing. We also recorded how often each item was used by all simulees. Person-parameter estimates based on CAT correlated higher than .90 with true values simulated. For all 1PL fitting item banks most simulees used more than 20 items but less than 30 items to reach the pre-set level of measurement error. However, testing based on item banks that complied to the 2PL revealed that, on average, only 10 items were sufficient to end testing at the same measurement error level. Both clearly demonstrate the precision and economy of computerized adaptive testing. Empirical evaluations from everyday uses will show whether these trends will hold up in practice. If so, CAT will become possible and reasonable with some 150 well-calibrated 2PL items.

Measurement error and person-specific reliability in multilevel autoregressive modeling.

2019 ◽  
Vol 24 (1) ◽  
pp. 70-91 ◽  
Author(s):  
Noémi K. Schuurman ◽  
Ellen L. Hamaker
Keyword(s):  
Measurement Error ◽  
Autoregressive Modeling

Technical Memoranda. Measurement error for six port ana

1990 ◽  
Vol 137 (6) ◽  
pp. 415 ◽  
Author(s):  
E. Bergeault ◽  
B. Huyart ◽  
G. Geneves ◽  
L. Jallet
Keyword(s):  
Measurement Error

Zirconia thickness measurements for irradiated fuel rods: an approach to better understanding measurement error

2011 ◽  
pp. 107-114
Author(s):  
B. Lacroix ◽  
T. Martella ◽  
M. Pras ◽  
M. Masson-Fauchier ◽  
L. Fayette
Keyword(s):  
Measurement Error ◽  
Fuel Rods ◽  
Thickness Measurements ◽  
Irradiated Fuel

Mathematical simulation of error functions of decision-making at tolerance control of measuring techniques availability

Metrologiya ◽  
2020 ◽  
pp. 3-15
Author(s):  
Rustam Z. Khayrullin ◽  
Alexey S. Kornev ◽  
Andrew A. Kostoglotov ◽  
Sergey V. Lazarenko
Keyword(s):  
Measurement Error ◽  
Geometric Interpretation ◽  
Measuring Instruments ◽  
Measured Quantity ◽  
Metrological Examination ◽  
Technical Documentation ◽  
Error Functions ◽  
Measuring Techniques ◽  
Tolerance Control ◽  
Laws Of Distribution

Analytical and computer models of false failure and undetected failure (error functions) were developed with tolerance control of the parameters of the components of the measuring technique. A geometric interpretation of the error functions as two-dimensional surfaces is given, which depend on the tolerance on the controlled parameter and the measurement error. The developed models are applicable both to theoretical laws of distribution, and to arbitrary laws of distribution of the measured quantity and measurement error. The results can be used in the development of metrological support of measuring equipment, the verification of measuring instruments, the metrological examination of technical documentation and the certification of measurement methods.

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