scholarly journals A MULTILEVEL MODEL OF A PARABOLIC ANTENNA MIRROR SEGMENT FOR ANALYZING THE SENSITIVITY OF POWER CHARACTERISTICS TO A DESIGN FACTOR

2020 ◽  
Author(s):  
Е.М. Рейзмунт
Keyword(s):  
Multilevel Model ◽  
Design Factor ◽  
Power Characteristics ◽  
Parabolic Antenna

Предложена и апробирована технология изучения влияния конструктивных решений на результирующие характеристики изделия на примере сегмента зеркала крупногабаритной параболической антенны. Выбраны силовые характеристики конструкции для статического и динамического анализа. Определен перечень конструктивных решений, влияние которых на результирующие характеристики представляет интерес, и разработана соответствующая система численных моделей. Новизна подхода заключается в построении многомерного и многоуровневого графа-модели, отражающего логику взаимосвязей конструктивных решений при разработке рассматриваемого объекта.

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 95-108 ◽  
Author(s):  
Steffen Nestler ◽  
Katharina Geukes ◽  
Mitja D. Back
Keyword(s):  
Multilevel Model ◽  
Multilevel Models ◽  
Mixed Effects ◽  
Repeated Measurements ◽  
Scale Model ◽  
Suggested Approach ◽  
Psychological Study ◽  
Level Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

A multilevel model of justice climate and legal claiming behaviors

2010 ◽  
Author(s):  
Cody L. Chullen
Keyword(s):  
Multilevel Model ◽  
Justice Climate

Employee well-being: A multilevel model linking work and family domains

2007 ◽  
Author(s):  
Kelly M. Schwind ◽  
Remus Ilies ◽  
Daniel Heller
Keyword(s):  
Multilevel Model ◽  
Well Being ◽  
Work And Family

DEPENDENCES OF POWER CHARACTERISTICS OF CIRCUIT AT CHARGE OF SUPERCAPACITORS

2016 ◽  
Vol 2016 (1) ◽  
pp. 3-10 ◽  
Author(s):  
O.A. Beletsky ◽  
◽  
N.I. Suprunovska ◽  
A.A. Shcherba ◽  
◽  
...  
Keyword(s):  
Power Characteristics

Power Characteristics of the Uniflow Hydrodynamic Sound Source Under the Conditions of Hydrostatic Pressure

2006 ◽  
Vol 33 (3) ◽  
pp. 278-285
Author(s):  
Yu. M. Dudzinskii ◽  
A. O. Sukharkov ◽  
N. V. Manicheva
Keyword(s):  
Hydrostatic Pressure ◽  
Sound Source ◽  
Power Characteristics

SPATIAL AND POWER CHARACTERISTICS OF FOCUSED MODES OF THE METAL CAVITY OF A TERAHERTZ LASER

2019 ◽  
Vol 78 (5) ◽  
pp. 373-383 ◽  
Author(s):  
S. A. Vlasenko ◽  
А. V. Degtyarev ◽  
M. M. Dubinin ◽  
V. A. Maslov
Keyword(s):  
Power Characteristics

Predictors of grit: A multilevel model examination of demographics and school experiences

2018 ◽  
Author(s):  
Dana Wanzer
Keyword(s):  
Academic Success ◽  
School Culture ◽  
Multilevel Modeling ◽  
Predictive Validity ◽  
School Engagement ◽  
Multilevel Model ◽  
School Experiences ◽  
School Level ◽  
School Demographics ◽  
And Gender

Much of the research on grit has examined its predictive validity toward academic success; however, little research has treated grit as an outcome. This study uses multilevel modeling to examine how student-level demographics, school-level demographics, and students’ experiences in school predict grit. Results demonstrate that students’ experiences in school—including school engagement, relationships with adults and peers, and school culture—and self-reported GPA were most strongly related to grit, ethnicity was weakly related to grit, and gender and school demographics did not significantly relate to grit. Implications of this research on the potential malleability of grit are discussed.

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