Hyunsoo Seol
hyunsooseol
Ph.D. majored in Educational Measurement & Applied Statistics at the Ohio State University, USA. And jamovi module developer.
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Top Repositories
Latent Class Analysis(LCA), LCA for ordinal indicators, Latent class growth modeling, Laten Profile Analysis, Rasch model, Linear Logistic Test Model, Rasch mixture model, linear and equipercentile equating can be performed within module.
This module is a tool for calculating correlations such as Partial, Tetrachoric, Intraclass correlation coefficients, Bootstrap agreement, Rater reliability, Generalizability Theory, Analytic Hierarchy Process, and allows users to produce Gaussian Graphical Model and Partial plot.
This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.
Latent Class analysis: This module allows users to conduct LCA, Multiple group LCA, and Multilevel LCA based on glca R package, and provide plot such as Profile plot and Radar chart within module.
This module includes Item Statistics, Model fit, Differential Item Functioning, Wright Map, Expected Scores Curve,and Item Characteristic Curve for DIF using MML estimation of the Rasch measurement model. Furthermore you can analyze DIF, Distractor analysis and Many facet Rasch model.
Repositories
93This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.
Latent Class analysis: This module allows users to conduct LCA, Multiple group LCA, and Multilevel LCA based on glca R package, and provide plot such as Profile plot and Radar chart within module.
Latent Class Analysis(LCA), LCA for ordinal indicators, Latent class growth modeling, Laten Profile Analysis, Rasch model, Linear Logistic Test Model, Rasch mixture model, linear and equipercentile equating can be performed within module.
This module includes Item Statistics, Model fit, Differential Item Functioning, Wright Map, Expected Scores Curve,and Item Characteristic Curve for DIF using MML estimation of the Rasch measurement model. Furthermore you can analyze DIF, Distractor analysis and Many facet Rasch model.
This module is a tool for calculating correlations such as Partial, Tetrachoric, Intraclass correlation coefficients, Bootstrap agreement, Rater reliability, Generalizability Theory, Analytic Hierarchy Process, and allows users to produce Gaussian Graphical Model and Partial plot.
No description provided.
Distribute and run LLMs with a single file.
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What the Package Does (One Line, Title Case)
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Meta-Analysis for JAMOVI
No description provided.
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jamovi module to build statistical charts (histogram, boxplot, point, bar, line...) with many options along with Likert and multiple response barplots.
No description provided.
Web R 실습 데이터
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ROC Analysis with Diagnostic Accuracy Tools for Jamovi
An open source alternative to Tableau. Embeddable visual analytic
Linear Models & Path Models
No description provided.
Functions for Medical Decision Making for ClinicoPath jamovi Module
ClinicoPath jamovi module Descriptives
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JAMOVI Frontend for Continuous Norming with cNORM
wrapper functions to use ggstatsplot functions as a module in jamovi
flexplot: graphical data analysis
survival functions in ClinicoPath jamovi module
No description provided.