The Probabilistic Dominance Model: Monotone Homogeneity

2014 ◽  
pp. 46-56
Keyword(s):  
Dominance Model

Modeling Self-Determination Theory Motivation Data by Using Unfolding IRT

2020 ◽  
pp. 1-9
Author(s):  
Philipp A. Freund ◽  
Annette Lohbeck
Keyword(s):  
Ideal Point ◽  
Self Determination Theory ◽  
Self Determination ◽  
Dominance Model ◽  
Irt Model ◽  
Autonomous Behavior ◽  
Location Parameters ◽  
Unfolding Models ◽  
Using Data ◽  
Item Location

Abstract. Self-determination theory (SDT) suggests that the degree of autonomous behavior regulation is a characteristic of distinct motivation types which thus can be ordered on the so-called Autonomy-Control Continuum (ACC). The present study employs an item response theory (IRT) model under the ideal point response/unfolding paradigm in order to model the response process to SDT motivation items in theoretical accordance with the ACC. Using data from two independent student samples (measuring SDT motivation for the academic subjects of Mathematics and German as a native language), it was found that an unfolding model exhibited a relatively better fit compared to a dominance model. The item location parameters under the unfolding paradigm showed clusters of items representing the different regulation types on the ACC to be (almost perfectly) empirically separable, as suggested by SDT. Besides theoretical implications, perspectives for the application of ideal point response/unfolding models in the development of measures for non-cognitive constructs are addressed.

Direct lepton production in the generalized vector-dominance model

1976 ◽  
Vol 13 (11) ◽  
pp. 3135-3138 ◽  
Author(s):  
E. N. Argyres ◽  
A. P. Contogouris ◽  
C. S. Lam
Keyword(s):  
Dominance Model ◽  
Lepton Production ◽  
Vector Dominance

The effects of using the wrong genetic model to predict the merit of crossbred genotypes

1989 ◽  
Vol 49 (2) ◽  
pp. 209-216 ◽  
Author(s):  
B. P. Kinghorn ◽  
P. E. Vercoe
Keyword(s):  
Pregnancy Rate ◽  
Epistatic Interaction ◽  
Genetic Model ◽  
Dominance Model ◽  
Epistatic Effects ◽  
Decision Errors ◽  
In Pregnancy

ABSTRACTThis paper evaluates the consequences of using the wrong genetic model when predicting the merit of previously untested crossbred genotypes. Eight models are considered, seven including different biological interpretations of two-locus epistatic interaction, plus one excluding epistatic effects. Published results from 13 genotypes generated from Hereford and Angus parental breeds were analysed, and predictions of a further seven genotypes made using different models. Under a dominance model, the predicted superiority in pregnancy rate (%) of a ¾ Hereford: ¼ Angus composite over a two-breed rotation was +1·2%, yet under all other models this was a negative value ranging from –1·9% to –3·7%. However, few such cases were found in which significant decision errors could conceivably be made. It is concluded that decisions on the choice of crossbred genotypes are generally quite robust to differences in the genetic model of the type studied here

scholarly journals Polymorphisms of Fatty Acid Elongase 2 Gene Afftects Risk of Pulmonary Tuberculosis in China Han Population

2021 ◽  
Author(s):  
Min Mu ◽  
Li Jing ◽  
Yuan-Jie Zou ◽  
Xing-Rong Tao ◽  
Fei Wang ◽  
...  
Keyword(s):  
Epidemiological Survey ◽  
Nucleotide Polymorphism ◽  
Dominance Model ◽  
Fatty Acid Elongase ◽  
Single Nucleotide ◽  
Female Population ◽  
Genetic Modeling ◽  
Male Patients ◽  
The Relationship ◽  
Control Study

Background: As an infectious disease closely related to Mycobacterium tuberculosis, autoimmunity, inflammation, environment and heredity, the relationship between the single nucleotide polymorphism of elongase 2 gene and the susceptibility to tuberculosis is still unknown. Methods: Between January 2016 and November 2018, a hospital-based case-control study was conducted. This epidemiological survey was conducted in both hospitals every three months. rs3798719, rs1570069, and rs2236212 in ELOVL2 gene were detected by Sanger sequencing. Results: Stratified by gender, the genotypes and allele frequencies of rs3798719, rs1570069 and rs2236212 showed significant differences between the two groups (χ2 = 6.987, P = 0.030), Genetic modeling showed that rs3798719 was statistically different in the overdominance model (χ2 = 4.784, OR = 1.414, 95% CI: 1.036-1.929, P < 0.05). The polymorphism of rs2236212 between male TB patients and healthy controls was statistically different in the dominance model. (χ2 = 4.192, OR = 0.507; 95% CI: 0.262-0.981, P < 0.05). Conclusion: The rs3798719 of ELOVL2 gene may be associated with susceptibility to TB in female population and the rs2236212 of ELOVL2 gene may be associated with TB incidence in male patients.

scholarly journals Merging methods of speech visualization

2005 ◽  
Vol 40 ◽  
pp. 19-32
Author(s):  
Sascha Fagel
Keyword(s):  
Speech Synthesis ◽  
Facial Feature ◽  
Visual Speech ◽  
Reference Image ◽  
Audiovisual Speech ◽  
Dominance Model ◽  
Rule Based ◽  
Face Model ◽  
Visual Speech Synthesis ◽  
Displacement Vectors

The author presents MASSY, the MODULAR AUDIOVISUAL SPEECH SYNTHESIZER. The system combines two approaches of visual speech synthesis. Two control models are implemented: a (data based) di-viseme model and a (rule based) dominance model where both produce control commands in a parameterized articulation space. Analogously two visualization methods are implemented: an image based (video-realistic) face model and a 3D synthetic head. Both face models can be driven by both the data based and the rule based articulation model. The high-level visual speech synthesis generates a sequence of control commands for the visible articulation. For every virtual articulator (articulation parameter) the 3D synthetic face model defines a set of displacement vectors for the vertices of the 3D objects of the head. The vertices of the 3D synthetic head then are moved by linear combinations of these displacement vectors to visualize articulation movements. For the image based video synthesis a single reference image is deformed to fit the facial properties derived from the control commands. Facial feature points and facial displacements have to be defined for the reference image. The algorithm can also use an image database with appropriately annotated facial properties. An example database was built automatically from video recordings. Both the 3D synthetic face and the image based face generate visual speech that is capable to increase the intelligibility of audible speech. Other well known image based audiovisual speech synthesis systems like MIKETALK and VIDEO REWRITE concatenate pre-recorded single images or video sequences, respectively. Parametric talking heads like BALDI control a parametric face with a parametric articulation model. The presented system demonstrates the compatibility of parametric and data based visual speech synthesis approaches.  

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