Showing 7 of total 7 results (show query)
yrosseel
lavaan:Latent Variable Analysis
Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.
Maintained by Yves Rosseel. Last updated 2 days ago.
factor-analysisgrowth-curve-modelslatent-variablesmissing-datamultilevel-modelsmultivariate-analysispath-analysispsychometricsstatistical-modelingstructural-equation-modeling
455 stars 16.81 score 8.4k scripts 217 dependents
jamovi
jmv:The 'jamovi' Analyses
A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).
Maintained by Jonathon Love. Last updated 1 months ago.
60 stars 9.48 score 440 scripts
dgerbing
lessR:Less Code, More Results
Each function replaces multiple standard R functions. For example, two function calls, Read() and CountAll(), generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for summary statistics via pivot tables, a comprehensive regression analysis, ANOVA and t-test, visualizations including the Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, time series with aggregation and forecasting, color themes, and Trellis (facet) graphics. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, generation and rendering of regression instructions for interpretative output, and interactive visualizations.
Maintained by David W. Gerbing. Last updated 18 days ago.
6 stars 7.42 score 394 scripts 3 dependents
zhenghuanie
sem:Structural Equation Models
Functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.
Maintained by Zhenghua Nie. Last updated 7 months ago.
7.09 score 310 scripts 43 dependents
fatelarico
FinNet:Quickly Build and Manipulate Financial Networks
Providing classes, methods, and functions to deal with financial networks. Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'. Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network'). There are also ad-hoc functions for the Fiedler value, global network efficiency, and cascade-failure analysis.
Maintained by Fabio Ashtar Telarico. Last updated 5 months ago.
2 stars 4.78 score 7 scripts
pmair78
cfa:Configural Frequency Analysis (CFA)
Analysis of configuration frequencies for simple and repeated measures, multiple-samples CFA, hierarchical CFA, bootstrap CFA, functional CFA, Kieser-Victor CFA, and Lindner's test using a conventional and an accelerated algorithm.
Maintained by Patrick Mair. Last updated 1 years ago.
1.78 score 60 scripts
reyar
Statsomat:Shiny Apps for Automated Data Analysis and Automated Interpretation
Shiny apps for automated data analysis, annotated outputs and human-readable interpretation in natural language. Designed especially for learners and applied researchers. Currently available methods: EDA, EDA with Python, Correlation Analysis, Principal Components Analysis, Confirmatory Factor Analysis.
Maintained by Denise Welsch. Last updated 3 years ago.
1.00 score 6 scripts