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 1 months ago

simulationstate-space-modelopenblascppopenmp

5.78 score 1 stars 2 dependents 75 scripts 554 downloads

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>.

Last updated 2 months ago

confidence-intervalsmonte-carlostructural-equation-modeling

5.39 score 2 stars 76 scripts 333 downloads

cTMed - Continuous Time Mediation

Calculates standard errors and confidence intervals for effects in continuous-time mediation models. This package extends the work of Deboeck and Preacher (2015) <doi:10.1080/10705511.2014.973960> and Ryan and Hamaker (2021) <doi:10.1007/s11336-021-09767-0> by providing methods to generate standard errors and confidence intervals for the total, direct, and indirect effects in these models.

Last updated 27 days ago

centralitycontinuous-timedelta-methodmediationmonte-carlo-methodnetworkopenblascppopenmp

4.56 score 24 scripts 394 downloads

betaMC - 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 2 months ago

confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients

4.27 score 1 stars 22 scripts 364 downloads

betaDelta - 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 2 months ago

confidence-intervalsdelta-method-standard-errorsstandardized-regression-coefficients

4.20 score 20 scripts 349 downloads

betaNB - 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().

Last updated 2 months ago

confidence-intervalsnonparametric-bootstrapregression-effect-sizesstandardized-regression-coefficients

4.16 score 1 stars 18 scripts 362 downloads

betaSandwich - 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 2 months ago

confidence-intervalsheteroskedasticity-consistent-standard-errorsstandardized-regression-coefficients

4.11 score 16 scripts 327 downloads

bootStateSpace - 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. 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 1 months ago

bootstrapstate-space-model

4.01 score 51 scripts 386 downloads