[.plcp_multi_power      Subset function for 'plcp_multi_power'-objects
as.data.frame.plcp_multi_sim_summary
                        Convert a multi-sim summary object to a tidy
                        data.frame
cohend                  Use Cohen's d as the effect size in
                        'study_parameters'
create_lmer_formula     Create an lmer formula based on a
                        'study_parameters'-object
dropout_manual          Manually specify dropout per time point
dropout_weibull         Use the Weibull distribution to specify the
                        dropout process
get_DEFT                Calculate the design effect and Type I errors
get_ICC_pre_clusters    Calculate the amount of baseline variance at
                        the cluster level
get_ICC_pre_subjects    Calculate the subject-level ICC at pretest
get_ICC_slope           Calculate the amount of slope variance at the
                        third level
get_VPC                 Calculate the variance partitioning coefficient
get_correlation_matrix
                        Calculate the subject-level (ICC) correlations
                        among time points
get_dropout             Get the amount of dropout
get_monte_carlo_se      Calculate the Monte Carlo standard error of the
                        empirical power estimates
get_power               Calculate power for two- and three-level models
                        with missing data.
get_power_table         Create a power table for a combination of
                        parameter values
get_sds                 Calculate the model implied standard deviations
                        per time point
get_slope_diff          Return the raw difference between the groups at
                        posttest
get_var_ratio           Calculates the ratio of the slope variance to
                        the within-subjects error variance
per_treatment           Setup parameters that differ per treatment
                        group
plot.plcp               Plot method for 'study_parameters'-objects
plot.plcp_ICC2          Plot method for
                        'get_correlation_matrix'-objects
plot.plcp_VPC           Plot method for 'get_VPC'-objects
plot.plcp_power_table   Plot method for 'get_power_table'-objects
plot.plcp_sds           Plot method for 'get_sds'-objects
powerlmm                Power Analysis for Longitudinal Multilevel
                        Models
print.plcp_2lvl         Print method for two-level
                        'study_parameters'-objects
print.plcp_3lvl         Print method for three-level
                        'study_parameters'-objects
print.plcp_ICC2         Print method for
                        'get_correlation_matrix'-objects
print.plcp_VPC          Print method for 'get_vpc'-objects
print.plcp_mc_se        Print method for 'get_monte_carlo_se'-objects
print.plcp_multi        Print method for
                        'study_parameters'-multiobjects
print.plcp_multi_power
                        Print method for 'get_power'-multi
print.plcp_multi_sim    Print method for 'simulate.plcp_multi'-objects
print.plcp_multi_sim_summary
                        Print method for
                        'summary.plcp_multi_sim'-objects
print.plcp_power_2lvl   Print method for two-level 'get_power'
print.plcp_power_3lvl   Print method for three-level 'get_power'
print.plcp_sds          Print method for 'get_sds'-objects
print.plcp_sim          Print method for 'simulate.plcp'-objects
print.plcp_sim_formula
                        Print method for simulation formulas
print.plcp_sim_summary
                        Print method for 'summary.plcp_sim'-objects
shiny_powerlmm          Launch powerlmm's Shiny web application
sim_formula             Create a simulation formula
sim_formula_compare     Compare multiple simulation formulas
simulate.plcp           Perform a simulation study using a
                        'study_parameters'-object
simulate_data           Generate a data set using a
                        'study_parameters'-object
study_parameters        Setup study parameters
summary.plcp_multi_sim
                        Summarize simulations based on a combination of
                        multiple parameter values
summary.plcp_sim        Summarize the results from a simulation of a
                        single study design-object
transform_to_posttest   Helper to transform the simulated longitudinal
                        'data.frame'
unequal_clusters        Setup unbalanced cluster sizes
update.plcp             Update a 'study_parameters'-object with new
                        settings
