simStateSpace - Simulate Data from State Space Models
Provides a streamlined and user-friendly framework for simulating data in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. This package was designed to generate data for the simulations performed in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.
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simulationstate-space-modelopenblascppopenmp
6.13 score 2 stars 4 dependents 62 scripts 724 downloadssemmcci - 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 (2024) <doi:10.3758/s13428-023-02114-4>.
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confidence-intervalsmonte-carlostructural-equation-modeling
4.77 score 1 stars 1 dependents 66 scripts 261 downloadsfitVARMxID - Fit the Vector Autoregressive Model for Multiple Individuals
Fit the vector autoregressive model for multiple individuals using the 'OpenMx' package (Hunter, 2017 <doi:10.1080/10705511.2017.1369354>).
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4.55 score 1 dependents 34 scripts 338 downloadsmetaDyn - Multivariate Meta-Analysis of Dynamic Model Estimates
Fits fixed-, random-, or mixed-effects multivariate meta-analysis models using dynamic model estimates from each individual building on and extending Lee and Gates (2023) <doi:10.1080/00273171.2023.2229310>.
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4.08 score 22 scripts 392 downloadscTMed - Continuous-Time Mediation
Computes effect sizes, standard errors, and confidence intervals for total, direct, and indirect effects in continuous-time mediation models as described in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.
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centralitycontinuous-timedelta-methodmediationmonte-carlo-methodnetworkopenblascppopenmp
4.00 score 1 stars 22 scripts 151 downloadsbootStateSpace - Bootstrap for State Space Models
Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. The parametric bootstrap implemented here was developed and applied in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.
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bootstrapstate-space-model
3.88 score 1 stars 50 scripts 144 downloadsbetaDelta - Confidence Intervals for Standardized Regression Coefficients
Generates confidence intervals for standardized regression coefficients using delta method standard errors for models fitted by lm() as described in Yuan and Chan (2011) <doi:10.1007/s11336-011-9224-6> and Jones and Waller (2015) <doi:10.1007/s11336-013-9380-y>. The package can also be used to generate confidence intervals for differences of standardized regression coefficients and as a general approach to performing the delta method. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
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confidence-intervalsdelta-method-standard-errorsstandardized-regression-coefficients
3.50 score 21 scripts 285 downloadsbetaSandwich - Robust Confidence Intervals for Standardized Regression Coefficients
Generates robust confidence intervals for standardized regression coefficients using heteroskedasticity-consistent standard errors for models fitted by lm() as described in Dudgeon (2017) <doi:10.1007/s11336-017-9563-z>. The package can also be used to generate confidence intervals for R-squared, adjusted R-squared, and differences of standardized regression coefficients. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.
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confidence-intervalsheteroskedasticity-consistent-standard-errorsstandardized-regression-coefficients
3.38 score 16 scripts 247 downloadsbetaMC - Monte Carlo for Regression Effect Sizes
Generates Monte Carlo confidence intervals for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm(). 'betaMC' combines ideas from Monte Carlo confidence intervals for the indirect effect (Pesigan and Cheung, 2024 <doi:10.3758/s13428-023-02114-4>) and the sampling covariance matrix of regression coefficients (Dudgeon, 2017 <doi:10.1007/s11336-017-9563-z>) to generate confidence intervals effect sizes in regression.
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confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients
3.34 score 1 stars 22 scripts 270 downloadsbetaNB - Bootstrap for Regression Effect Sizes
Generates nonparametric bootstrap confidence intervals (Efron and Tibshirani, 1993: <doi:10.1201/9780429246593>) for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm().
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confidence-intervalsnonparametric-bootstrapregression-effect-sizesstandardized-regression-coefficients
3.26 score 1 stars 18 scripts 238 downloads