Bayesian Super Imposition by Translation and Rotation Growth Curve Analysis

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Documentation for package ‘bsitar’ version 0.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

add_model_criterion	Add model fit criteria to model
add_model_criterion.bgmfit	Add model fit criteria to model
berkeley	Berkeley Child Guidance Study Data
berkeley_exdata	Berkeley Child Guidance Study Data for females
berkeley_exfit	Model fit to the Berkeley Child Guidance Study Data for females
bsitar	Fit Bayesian SITAR growth curve model
expose_model_functions	Expose user defined Stan function for post-processing
expose_model_functions.bgmfit	Expose user defined Stan function for post-processing
fitted_draws	Fitted (expected) values from the posterior draws
fitted_draws.bgmfit	Fitted (expected) values from the posterior draws
getNsObject	Check and get namespace object if exists
growthparameters	Estimate growth parameters from the model fit
growthparameters.bgmfit	Estimate growth parameters from the model fit
growthparameters_comparison	Compare growth parameters
growthparameters_comparison.bgmfit	Compare growth parameters
loo_validation	Perform leave-one-out (loo) cross-validation
loo_validation.bgmfit	Perform leave-one-out (loo) cross-validation
marginal_comparison	Compare growth curves
marginal_comparison.bgmfit	Compare growth curves
marginal_draws	Fitted (expected) values from the posterior draws
marginal_draws.bgmfit	Fitted (expected) values from the posterior draws
optimize_model	Optimize SITAR model
optimize_model.bgmfit	Optimize SITAR model
plot_conditional_effects	Visualize conditional effects of predictor
plot_conditional_effects.bgmfit	Visualize conditional effects of predictor
plot_curves	Plot growth curves
plot_curves.bgmfit	Plot growth curves
plot_ppc	Perform posterior predictive distribution checks
plot_ppc.bgmfit	Perform posterior predictive distribution checks
predict_draws	Predicted values from the posterior predictive distribution
predict_draws.bgmfit	Predicted values from the posterior predictive distribution
update_model	Update model
update_model.bgmfit	Update model