What is he best known for?
The fields of study he is best known for:
- Statistics
- Machine learning
- Regression analysis
Tenko Raykov mainly focuses on Structural equation modeling, Statistics, Econometrics, Scale and Reliability.
His work in Structural equation modeling covers topics such as Applied mathematics which are related to areas like Interval.
Tenko Raykov works mostly in the field of Statistics, limiting it down to topics relating to Composite number and, in certain cases, Sample.
The study incorporates disciplines such as Equivalence, Confirmatory factor analysis, Estimation theory, Multivariate analysis and Empirical research in addition to Econometrics.
Along with Scale, other disciplines of study including Cronbach's alpha, Interval estimation, Mathematical optimization, Reliability and Latent variable model are integrated into his research.
His Latent variable model research integrates issues from Data mining and Psychometrics.
His most cited work include:
- A First Course in Structural Equation Modeling (872 citations)
- Estimation of composite reliability for congeneric measures. (836 citations)
- Introduction to Psychometric Theory (354 citations)
What are the main themes of his work throughout his whole career to date?
Tenko Raykov mostly deals with Statistics, Econometrics, Latent variable model, Structural equation modeling and Interval estimation.
His work on Reliability, Confidence interval, Covariance and Cronbach's alpha as part of general Statistics study is frequently connected to Scale, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His work investigates the relationship between Econometrics and topics such as Multivariate analysis that intersect with problems in Multivariate statistics.
His research integrates issues of Statistical hypothesis testing, Data mining and Measurement invariance in his study of Latent variable model.
His study focuses on the intersection of Structural equation modeling and fields such as Psychometrics with connections in the field of Confirmatory factor analysis.
He combines subjects such as Computation, Multilevel model and Interval with his study of Interval estimation.
He most often published in these fields:
- Statistics (47.32%)
- Econometrics (38.39%)
- Latent variable model (31.25%)
What were the highlights of his more recent work (between 2017-2021)?
- Latent variable model (31.25%)
- Statistics (47.32%)
- Econometrics (38.39%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Latent variable model, Statistics, Econometrics, Interval estimation and Item response theory.
His research integrates issues of Multilevel model, Data mining and Criterion validity in his study of Latent variable model.
His Criterion validity research is multidisciplinary, incorporating elements of Dependency, Statistical hypothesis testing, Structural equation modeling and Predictive validity.
Tenko Raykov has included themes like Empirical research and Latent variable in his Econometrics study.
Within one scientific family, Tenko Raykov focuses on topics pertaining to Interval under Interval estimation, and may sometimes address concerns connected to Regression analysis, Multicollinearity, Variance inflation factor and Linear regression.
His study looks at the relationship between Cronbach's alpha and topics such as Alpha, which overlap with Factorial and Reliability.
Between 2017 and 2021, his most popular works were:
- Thanks Coefficient Alpha, We Still Need You!. (36 citations)
- Evaluation of Variance Inflation Factors in Regression Models Using Latent Variable Modeling Methods (9 citations)
- Studying Latent Criterion Validity for Complex Structure Measuring Instruments Using Latent Variable Modeling (6 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Machine learning
- Regression analysis
The scientist’s investigation covers issues in Statistics, Item response theory, Econometrics, Interval estimation and Spurious relationship.
His Statistical hypothesis testing, Criterion validity, Predictive validity and Structural equation modeling study, which is part of a larger body of work in Statistics, is frequently linked to Variable, bridging the gap between disciplines.
His research in the fields of Polytomous Rasch model overlaps with other disciplines such as Point and Set.
His Econometrics research is multidisciplinary, incorporating perspectives in Empirical research, Alpha and Reliability.
The study incorporates disciplines such as Latent variable model, Classical test theory and Natural language processing in addition to Interval estimation.
In Latent variable model, he works on issues like Interval, which are connected to Explained variation and Item analysis.
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