Adaptive Measurement of Individual Change

2008 ◽  
Vol 216 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Gyenam Kim-Kang ◽  
David J. Weiss
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Entire Range ◽  
Individual Change ◽  
Measurement Of Change ◽  
Adaptive Measurement

Adaptive measurement of change (AMC) was investigated by examining the recovery of true change. Monte Carlo simulation was used to compare three conventional testing (CT) methods with AMC. The CTs estimated individual change moderately well when the test was highly discriminating and when the θ level matched the test difficulty. However, AMC measured individual change equally well across the entire range of θ. AMC with more discriminating items produced the most precise estimates of individual change. AMC was shown to be superior to CTs under all conditions examined. In addition, AMC is efficient – it can dramatically reduce the number of items necessary to measure individual change. The results indicate that AMC is a viable and effective method for measuring individual change.

Robustness of Adaptive Measurement of Change to Item Parameter Estimation Error

2021 ◽  
pp. 001316442110339
Author(s):  
Allison W. Cooperman ◽  
David J. Weiss ◽  
Chun Wang
Keyword(s):  
Parameter Estimation ◽  
False Positive ◽  
Estimation Error ◽  
Latent Trait ◽  
Item Bank ◽  
Item Parameter ◽  
Individual Change ◽  
Measurement Of Change ◽  
Item Parameter Estimation ◽  
Adaptive Measurement

Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests—a Z test, likelihood ratio test, and score ratio index—have demonstrated desirable statistical properties in this context, including low false positive rates and high true positive rates. However, the extant AMC research has assumed that the item parameter values in the simulated item banks were devoid of estimation error. This assumption is unrealistic for applied testing settings, where item parameters are estimated from a calibration sample before test administration. Using Monte Carlo simulation, this study evaluated the robustness of the common AMC hypothesis tests to the presence of item parameter estimation error when measuring omnibus change across four testing occasions. Results indicated that item parameter estimation error had at most a small effect on false positive rates and latent trait change recovery, and these effects were largely explained by the computerized adaptive testing item bank information functions. Differences in AMC performance as a function of item parameter estimation error and choice of hypothesis test were generally limited to simulees with particularly low or high latent trait values, where the item bank provided relatively lower information. These simulations highlight how AMC can accurately measure intra-individual change in the presence of item parameter estimation error when paired with an informative item bank. Limitations and future directions for AMC research are discussed.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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