Robust Bayesian Approaches in Growth Curve Modeling: Using Student's t Distributions versus a Semiparametric Method
In: Structural equation modeling: a multidisciplinary journal, Band 27, Heft 4, S. 544-560
ISSN: 1532-8007
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In: Structural equation modeling: a multidisciplinary journal, Band 27, Heft 4, S. 544-560
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 25, Heft 4, S. 650-658
ISSN: 1532-8007
In: Behaviormetrika, Band 44, Heft 2, S. 447-476
ISSN: 1349-6964
In: Structural equation modeling: a multidisciplinary journal, Band 18, Heft 1, S. 18-34
ISSN: 1532-8007
Microwave-absorbing materials are widely used in numerous fields, including the military, daily protection, etc. Currently, in addition to being lightweight and highly efficient, good film-forming processing characteristics and environmental stability are also required for the practical application of microwave-absorbing materials, which, in general, are difficult to make compatible. In this paper, a mulberry-like PDA/PPy/ND hierarchical structure was prepared by in situ polymerization. The hierarchical structure showed remarkably enhanced microwave absorption, as well as better flexible film-forming characteristics, thanks to the multiple roles PDA played in the system. The optimal RL peak for PDA/PPy/ND could reach −43.6 dB at 7.58 GHz, which is mainly attributed to the multiple dielectric loss paths and significantly improved impedance-matching characteristics. Furthermore, given the H-bond crosslink, the introduction of PDA also promoted the film formation and dispersion of PDA/PPy/ND in the PVA matrix, forming a water-resistant and flexible film. This work provides a referencing path for the design and practical applications of lightweight microwave-absorbing materials.
BASE
In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 1, S. 39-50
ISSN: 1532-8007
In: IMF Working Paper No. 16/68
SSRN
In: Structural equation modeling: a multidisciplinary journal, Band 19, Heft 4, S. 683-702
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 31, Heft 1, S. 14-26
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 25, Heft 5, S. 737-749
ISSN: 1532-8007
In: CAIE-D-22-01094
SSRN
In: HELIYON-D-22-34234
SSRN
In: Methodology in the social sciences
"Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--
In: Structural equation modeling: a multidisciplinary journal, Band 28, Heft 1, S. 148-161
ISSN: 1532-8007
In: Structural equation modeling: a multidisciplinary journal, Band 26, Heft 4, S. 623-635
ISSN: 1532-8007