hyunsooseol/snowIRT

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9
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Language
R
Created over 4 years ago
Updated 4 months ago

hyunsooseol/snowIRT

hyunsooseol

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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.

seolmatrix

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.

snowLatent

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.

snowCluster

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.

snowRMM

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.

jmvtools

Create "Correlations" jamovi module

RaschSim

Generating Rasch simulation dataset

BootFit

Bootstrap Item Fit statistics and 95% Confidence Interval using MML estimation in the Rasch model

text_mining

R을 이용한 텍스트 마이닝 교재 코드