Poster - Thurs Eve-25: Depth dependence of electron backscatter for electron radiotherapy: A Monte Carlo study

2008 ◽  
Vol 35 (7Part2) ◽  
pp. 3406-3406
Author(s):  
J Chow ◽  
A Owrangi
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Depth Dependence ◽  
Electron Backscatter ◽  
Electron Radiotherapy

scholarly journals Dosimetric evaluation of skin collimation with tungsten rubber for electron radiotherapy: A Monte Carlo study

2021 ◽  
Vol 22 (4) ◽  
pp. 63-70
Author(s):  
Kazuki Wakabayashi ◽  
Hajime Monzen ◽  
Mikoto Tamura ◽  
Kenji Matsumoto ◽  
Yoshiki Takei ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Electron Radiotherapy

Shielding disk position in intra-operative electron radiotherapy (IOERT): A Monte Carlo study

2018 ◽  
Vol 51 ◽  
pp. 1-6 ◽  
Author(s):  
Husein Alhamada ◽  
Stephane Simon ◽  
Catherine Philippson ◽  
Christophe Vandekerkhove ◽  
Younes Jourani ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Electron Radiotherapy

Evaluation of dosimetric properties of shielding disk used in intraoperative electron radiotherapy: A Monte Carlo study

2018 ◽  
Vol 139 ◽  
pp. 107-113 ◽  
Author(s):  
Mostafa Robatjazi ◽  
Hamid Reza Baghani ◽  
Seied Rabi Mahdavic ◽  
Giuseppe Felici
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Electron Radiotherapy

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study
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