R-universe search: topic:structural-equation-modeling

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-analysis growth-curve-models latent-variables missing-data multilevel-models multivariate-analysis path-analysis psychometrics statistical-modeling structural-equation-modeling

454 stars 16.82 score 8.4k scripts 218 dependents

ecmerkle

blavaan:Bayesian Latent Variable Analysis

Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models. References: Merkle & Rosseel (2018) <doi:10.18637/jss.v085.i04>; Merkle et al. (2021) <doi:10.18637/jss.v100.i06>.

Maintained by Edgar Merkle. Last updated 9 days ago.

bayesian-statistics factor-analysis growth-curve-models latent-variables missing-data multilevel-models multivariate-analysis path-analysis psychometrics statistical-modeling structural-equation-modeling cpp

92 stars 10.84 score 183 scripts 3 dependents

tbates

umx:Structural Equation Modeling and Twin Modeling in R

Quickly create, run, and report structural equation models, and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. <doi:10.1017/thg.2019.2>.

Maintained by Timothy C. Bates. Last updated 14 days ago.

behavior-genetics genetics openmx psychology sem statistics structural-equation-modeling tutorials twin-models umx

44 stars 9.45 score 472 scripts

mikewlcheung

metaSEM:Meta-Analysis using Structural Equation Modeling

A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices, see Cheung (2015) <doi:10.3389/fpsyg.2014.01521>.

Maintained by Mike Cheung. Last updated 21 days ago.

meta-analysis meta-analytic-sem missing-data multilevel-models multivariate-analysis structural-equation-modeling structural-equation-models

30 stars 9.43 score 208 scripts 1 dependents

brandmaier

semtree:Recursive Partitioning for Structural Equation Models

SEM Trees and SEM Forests -- an extension of model-based decision trees and forests to Structural Equation Models (SEM). SEM trees hierarchically split empirical data into homogeneous groups each sharing similar data patterns with respect to a SEM by recursively selecting optimal predictors of these differences. SEM forests are an extension of SEM trees. They are ensembles of SEM trees each built on a random sample of the original data. By aggregating over a forest, we obtain measures of variable importance that are more robust than measures from single trees. A description of the method was published by Brandmaier, von Oertzen, McArdle, & Lindenberger (2013) <doi:10.1037/a0030001> and Arnold, Voelkle, & Brandmaier (2020) <doi:10.3389/fpsyg.2020.564403>.

Maintained by Andreas M. Brandmaier. Last updated 3 months ago.

bigdata decision-tree forest multivariate randomforest recursive-partitioning sem statistical-modeling structural-equation-modeling structural-equation-models

15 stars 8.56 score 68 scripts

kss2k

modsem:Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)

Estimation of interaction (i.e., moderation) effects between latent variables in structural equation models (SEM). The supported methods are: The constrained approach (Algina & Moulder, 2001). The unconstrained approach (Marsh et al., 2004). The residual centering approach (Little et al., 2006). The double centering approach (Lin et al., 2010). The latent moderated structural equations (LMS) approach (Klein & Moosbrugger, 2000). The quasi-maximum likelihood (QML) approach (Klein & Muthén, 2007) (temporarily unavailable) The constrained- unconstrained, residual- and double centering- approaches are estimated via 'lavaan' (Rosseel, 2012), whilst the LMS- and QML- approaches are estimated via 'modsem' it self. Alternatively model can be estimated via 'Mplus' (Muthén & Muthén, 1998-2017). References: Algina, J., & Moulder, B. C. (2001). <doi:10.1207/S15328007SEM0801_3>. "A note on estimating the Jöreskog-Yang model for latent variable interaction using 'LISREL' 8.3." Klein, A., & Moosbrugger, H. (2000). <doi:10.1007/BF02296338>. "Maximum likelihood estimation of latent interaction effects with the LMS method." Klein, A. G., & Muthén, B. O. (2007). <doi:10.1080/00273170701710205>. "Quasi-maximum likelihood estimation of structural equation models with multiple interaction and quadratic effects." Lin, G. C., Wen, Z., Marsh, H. W., & Lin, H. S. (2010). <doi:10.1080/10705511.2010.488999>. "Structural equation models of latent interactions: Clarification of orthogonalizing and double-mean-centering strategies." Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). <doi:10.1207/s15328007sem1304_1>. "On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables." Marsh, H. W., Wen, Z., & Hau, K. T. (2004). <doi:10.1037/1082-989X.9.3.275>. "Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction." Muthén, L.K. and Muthén, B.O. (1998-2017). "'Mplus' User’s Guide. Eighth Edition." <https://www.statmodel.com/>. Rosseel Y (2012). <doi:10.18637/jss.v048.i02>. "'lavaan': An R Package for Structural Equation Modeling."

Maintained by Kjell Solem Slupphaug. Last updated 1 days ago.

interaction-effect interaction-effects latent-moderated-structural-equations lavaan-syntax lms moderation qml quasi-maximum-likelihood rlang rlanguage sem structural-equation-modeling structural-equation-models openblas cpp openmp

6 stars 8.41 score 54 scripts

sfcheung

manymome:Mediation, Moderation and Moderated-Mediation After Model Fitting

Computes indirect effects, conditional effects, and conditional indirect effects in a structural equation model or path model after model fitting, with no need to define any user parameters or label any paths in the model syntax, using the approach presented in Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>. Can also form bootstrap confidence intervals by doing bootstrapping only once and reusing the bootstrap estimates in all subsequent computations. Supports bootstrap confidence intervals for standardized (partially or completely) indirect effects, conditional effects, and conditional indirect effects as described in Cheung (2009) <doi:10.3758/BRM.41.2.425> and Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Model fitting can be done by structural equation modeling using lavaan() or regression using lm().

Maintained by Shu Fai Cheung. Last updated 1 months ago.

bootstrapping confidence-interval lavaan manymome mediation moderated-mediation moderation regression sem standardized-effect-size structural-equation-modeling

1 stars 8.06 score 172 scripts 4 dependents

jhorzek

lessSEM:Non-Smooth Regularization for Structural Equation Models

Provides regularized structural equation modeling (regularized SEM) with non-smooth penalty functions (e.g., lasso) building on 'lavaan'. The package is heavily inspired by the ['regsem'](<https://github.com/Rjacobucci/regsem>) and ['lslx'](<https://github.com/psyphh/lslx>) packages.

Maintained by Jannik H. Orzek. Last updated 1 years ago.

lasso psychometrics regularization regularized-structural-equation-model sem structural-equation-modeling openblas cpp openmp

7 stars 7.19 score 223 scripts

sfcheung

semptools:Customizing Structural Equation Modelling Plots

Most function focus on specific ways to customize a graph. They use a 'qgraph' output as the first argument, and return a modified 'qgraph' object. This allows the functions to be chained by a pipe operator.

Maintained by Shu Fai Cheung. Last updated 3 months ago.

diagram graph lavaan plot sem structural-equation-modeling

7 stars 7.12 score 87 scripts

rempsyc

lavaanExtra:Convenience Functions for Package 'lavaan'

Affords an alternative, vector-based syntax to 'lavaan', as well as other convenience functions such as naming paths and defining indirect links automatically, in addition to convenience formatting optimized for a publication and script sharing workflow.

Maintained by Rémi Thériault. Last updated 9 months ago.

convenience-functions lavaan psychology statistics structural-equation-modeling

18 stars 6.95 score 33 scripts

andrea-luciani

bimets:Time Series and Econometric Modeling

Time series analysis, (dis)aggregation and manipulation, e.g. time series extension, merge, projection, lag, lead, delta, moving and cumulative average and product, selection by index, date and year-period, conversion to daily, monthly, quarterly, (semi)annually. Simultaneous equation models definition, estimation, simulation and forecasting with coefficient restrictions, error autocorrelation, exogenization, add-factors, impact and interim multipliers analysis, conditional equation evaluation, rational expectations, endogenous targeting and model renormalization, structural stability, stochastic simulation and forecast, optimal control.

Maintained by Andrea Luciani. Last updated 4 months ago.

econometrics optimal-control simultaneous-equations stochastic-simulation structural-equation-modeling time-series

15 stars 6.13 score 30 scripts

sfcheung

semfindr:Influential Cases in Structural Equation Modeling

Sensitivity analysis in structural equation modeling using influence measures and diagnostic plots. Support leave-one-out casewise sensitivity analysis presented by Pek and MacCallum (2011) <doi:10.1080/00273171.2011.561068> and approximate casewise influence using scores and casewise likelihood.

Maintained by Shu Fai Cheung. Last updated 25 days ago.

diagnostics influential-cases lavaan outlier-detection sensitivity-analysis structural-equation-modeling

1 stars 6.03 score 90 scripts

sfcheung

semlbci:Likelihood-Based Confidence Interval in Structural Equation Models

Forms likelihood-based confidence intervals (LBCIs) for parameters in structural equation modeling, introduced in Cheung and Pesigan (2023) <doi:10.1080/10705511.2023.2183860>. Currently implements the algorithm illustrated by Pek and Wu (2018) <doi:10.1037/met0000163>, and supports the robust LBCI proposed by Falk (2018) <doi:10.1080/10705511.2017.1367254>.

Maintained by Shu Fai Cheung. Last updated 2 months ago.

confidence-intervals lavaan likelihood-based profile-likelihood structural-equation-modeling

1 stars 5.93 score 188 scripts

jhorzek

mxsem:Specify 'OpenMx' Models with a 'lavaan'-Style Syntax

Provides a 'lavaan'-like syntax for 'OpenMx' models. The syntax supports definition variables, bounds, and parameter transformations. This allows for latent growth curve models with person-specific measurement occasions, moderated nonlinear factor analysis and much more.

Maintained by Jannik H. Orzek. Last updated 4 months ago.

factor-analysis lavaan openmx structural-equation-modeling cpp

3 stars 5.93 score 47 scripts

sfcheung

lavaan.printer:Helper Functions for Printing 'lavaan' Outputs

Helpers for customizing selected outputs from 'lavaan' by Rosseel (2012) <doi:10.18637/jss.v048.i02> and print them. The functions are intended to be used by package developers in their packages and so are not designed to be user-friendly. They are designed to be let developers customize the tables by other functions. Currently the parameter estimates tables of a fitted object are supported.

Maintained by Shu Fai Cheung. Last updated 6 months ago.

lavaan structural-equation-modeling

5.78 score 4 scripts 1 dependents

wjschne

ggdiagram:Object-Oriented Diagram Plots with ggplot2

The ggdiagram package creates path diagrams with an object-oriented approach and plots diagrams with ggplot2.

Maintained by W. Joel Schneider. Last updated 5 days ago.

diagrams factor-analysis ggplot2 path-analysis s7 structural-equation-modeling

32 stars 5.43 score

jeksterslab

semmcci:Monte Carlo Confidence Intervals in Structural Equation Modeling

Monte Carlo confidence intervals for free and defined parameters in models fitted in the structural equation modeling package 'lavaan' can be generated using the 'semmcci' package. 'semmcci' has three main functions, namely, MC(), MCMI(), and MCStd(). The output of 'lavaan' is passed as the first argument to the MC() function or the MCMI() function to generate Monte Carlo confidence intervals. Monte Carlo confidence intervals for the standardized estimates can also be generated by passing the output of the MC() function or the MCMI() function to the MCStd() function. A description of the package and code examples are presented in Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.

confidence-intervals monte-carlo structural-equation-modeling

2 stars 5.39 score 76 scripts

alexanderrobitzsch

LAM:Some Latent Variable Models

Includes some procedures for latent variable modeling with a particular focus on multilevel data. The 'LAM' package contains mean and covariance structure modelling for multivariate normally distributed data (mlnormal(); Longford, 1987; <doi:10.1093/biomet/74.4.817>), a general Metropolis-Hastings algorithm (amh(); Roberts & Rosenthal, 2001, <doi:10.1214/ss/1015346320>) and penalized maximum likelihood estimation (pmle(); Cole, Chu & Greenland, 2014; <doi:10.1093/aje/kwt245>).

Maintained by Alexander Robitzsch. Last updated 9 months ago.

multilevel-models structural-equation-modeling openblas cpp

6 stars 5.30 score 11 scripts 1 dependents

sfcheung

semhelpinghands:Helper Functions for Structural Equation Modeling

An assortment of helper functions for doing structural equation modeling, mainly by 'lavaan' for now. Most of them are time-saving functions for common tasks in doing structural equation modeling and reading the output. This package is not for functions that implement advanced statistical procedures. It is a light-weight package for simple functions that do simple tasks conveniently, with as few dependencies as possible.

Maintained by Shu Fai Cheung. Last updated 5 months ago.

bootstrapping lavaan structural-equation-modeling

5.13 score 27 scripts

sfcheung

semlrtp:Likelihood Ratio Test P-Values for Structural Equation Models

Computes likelihood ratio test (LRT) p-values for free parameters in a structural equation model. Currently supports models fitted by the 'lavaan' package by Rosseel (2012) <doi:10.18637/jss.v048.i02>.

Maintained by Shu Fai Cheung. Last updated 2 months ago.

hypothesis-testing lavaan structural-equation-modeling

4.98 score 24 scripts

sfcheung

betaselectr:Betas-Select in Structural Equation Models and Linear Models

It computes betas-select, coefficients after standardization in structural equation models and regression models, standardizing only selected variables. Supports models with moderation, with product terms formed after standardization. It also offers confidence intervals that account for standardization, including bootstrap confidence intervals as proposed by Cheung et al. (2022) <doi:10.1037/hea0001188>.

Maintained by Shu Fai Cheung. Last updated 5 months ago.

bootstrapping confidence-intervals generalized-linear-models lavaan logistic-regression regression sem standardization structural-equation-modeling

1 stars 4.95 score 8 scripts

chkiefer

lavacreg:Latent Variable Count Regression Models

Estimation of a multi-group count regression models (i.e., Poisson, negative binomial) with latent covariates. This packages provides two extensions compared to ordinary count regression models based on a generalized linear model: First, measurement models for the predictors can be specified allowing to account for measurement error. Second, the count regression can be simultaneously estimated in multiple groups with stochastic group weights. The marginal maximum likelihood estimation is described in Kiefer & Mayer (2020) <doi:10.1080/00273171.2020.1751027>.

Maintained by Christoph Kiefer. Last updated 6 hours ago.

count-regression latent-covariates structural-equation-modeling openblas cpp openmp

3 stars 4.88 score 5 scripts

sfcheung

modelbpp:Model BIC Posterior Probability

Fits the neighboring models of a fitted structural equation model and assesses the model uncertainty of the fitted model based on BIC posterior probabilities, using the method presented in Wu, Cheung, and Leung (2020) <doi:10.1080/00273171.2019.1574546>.

Maintained by Shu Fai Cheung. Last updated 6 months ago.

lavaan model-comparison model-comparison-and-selection model-selection structural-equation-modeling

4.54 score 2 scripts

sfcheung

manymome.table:Publication-Ready Tables for 'manymome' Results

Converts results from the 'manymome' package, presented in Cheung and Cheung (2023) <doi:10.3758/s13428-023-02224-z>, to publication-ready tables.

Maintained by Shu Fai Cheung. Last updated 4 months ago.

lavaan manymome mediation moderated-mediation moderation regression sem structural-equation-modeling

4.00 score 2 scripts

alexanderrobitzsch

STARTS:Functions for the STARTS Model

Contains functions for estimating the STARTS model of Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>, <DOI:10.1037/10409-008>. Penalized maximum likelihood estimation and Markov Chain Monte Carlo estimation are also provided, see Luedtke, Robitzsch and Wagner (2018) <DOI:10.1037/met0000155>.

Maintained by Alexander Robitzsch. Last updated 1 years ago.

longitudinal-data structural-equation-modeling cpp

2 stars 3.85 score 14 scripts

mikewlcheung

symSEM:Symbolic Computation for Structural Equation Models

A collection of functions for symbolic computation using the 'caracas' package for structural equation models and other statistical analyses. Among its features is the ability to calculate the model-implied covariance (and correlation) matrix and the sampling covariance matrix of variable functions using the delta method.

Maintained by Mike Cheung. Last updated 11 months ago.

caracas structural-equation-modeling symbolic-calculations

4 stars 3.60 score 10 scripts