The project investigates the evolution of a Fuzzy delphi method module that has been incorporated into Jamovi and explores its potential uses and benefits.
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Updated
May 29, 2024 - R
The project investigates the evolution of a Fuzzy delphi method module that has been incorporated into Jamovi and explores its potential uses and benefits.
This module provides Latent Class Analysis, Laten Profile Analysis, Rasch model, Linear Logistic Test Model, and Rasch mixture model including model information,fit statistics,and bootstrap fit based on JMLE. Furthermore, 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.
jamovi - open software to bridge the gap between researcher and statistician
GAMLj: GLM, Mixed, Generalized and Generalized mixed models for jamovi
A jamovi module to calculate Student's and Welch's t-Test (including related Cohen's d) based on summary data (mean, standard deviation, and sample size), to comprehend reported tests.
Docs of jamovi Advanced Mediation Models
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.
Estimation Statistics with Confidence Intervals
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.
The Big Bang of Data Science- Analysis from the Start to The End- [Book Two]
ClinicoPath jamovi Module
Basic Statistical Methods for Social Science [Textbook]
A manual that provides a brief step-by-step instructions on data analysis using R and Jamovi.
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.
ClinicoPath jamovi module Descriptives
wrapper functions to use ggstatsplot functions as a module in jamovi
survival functions in ClinicoPath jamovi module
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