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. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010) <doi:10.1080/10705511003661553>.
Last updated 13 days ago
simulationstate-space-model
1 stars 2.37 score 2 dependenciessemmcci - 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>.
Last updated 13 days ago
confidence-intervalsmonte-carlostructural-equation-modeling
2 stars 2.28 score 64 dependenciesbetaMC - 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, 2023 <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.
Last updated 13 days ago
confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients
1 stars 2.20 score 0 dependenciesbetaSandwich - 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>.
Last updated 13 days ago
confidence-intervalsheteroskedasticity-consistent-standard-errorsstandardized-regression-coefficients
2.15 score 0 dependenciesbetaDelta - 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>.
Last updated 13 days ago
confidence-intervalsdelta-method-standard-errorsstandardized-regression-coefficients
2.15 score 1 dependenciesbetaNB - Bootstrap for Regression Effect Sizes
Generates nonparametric bootstrap confidence intervals (Efron & 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().
Last updated 13 days ago
confidence-intervalsnonparametric-bootstrapregression-effect-sizesstandardized-regression-coefficients
2.11 score 0 dependencies