Power Calculations for Longitudinal Multilevel Models


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Documentation for package ‘powerlmm’ version 0.1.0

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powerlmm-package Power Calculations for Longitudinal Multilevel Models
dropout_manual Manually specify dropout per time point
dropout_weibull Use the Weibull distribution to specify the dropout process
get_correlation_matrix Calculate the subject-level (ICC) correlations among time points
get_correlation_matrix.plcp_multi Calculate the subject-level (ICC) correlations among time points
get_DEFT Calculate the design effect and type 1 errors
get_DEFT.plcp_3lvl Calculate the design effect and type 1 errors
get_dropout Get the amount of dropout
get_dropout.plcp_multi Get the amount of dropout
get_ICC_pre_clusters Calculate the amount of baseline variance at the cluster level
get_ICC_pre_subjects Calculates the amount of baseline variance at the subject level
get_ICC_slope Calculate the amount of slope variance at the third level
get_monte_carlo_se Calculate the Monte Carlo standard error of the empirical power estimates
get_monte_carlo_se.plcp_power_2lvl Calculate the Monte Carlo standard error of the empirical power estimates
get_monte_carlo_se.plcp_power_3lvl 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_var_ratio Calculates the ratio of the slope variance to the within-subjects error variance
get_VPC Calculate the variance partitioning coefficient
get_VPC.plcp Calculate the variance partitioning coefficient
per_treatment Setup parameters that differ per treatment group
plot.plcp Plot method for 'study_parameters'-objects
plot.plcp_power_table Plot method for 'get_power_table'-objects
plot.plcp_sds Plot method for 'get_sds'-objects
plot.plcp_VPC Plot method for 'get_VPC'-objects
powerlmm Power Calculations 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_mc_se Print method for 'get_monte_carlo_se'-objects
print.plcp_multi_sim Print method for 'simulate.plcp_multi'-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_summary Print method for 'summary.plcp_sim'-objects
print.plcp_VPC Print method for 'get_vpc'-objects
shiny_powerlmm Launch powerlmm's Shiny web application
simulate.plcp Perform a simulation study using a 'study_parameters'-object
simulate.plcp_multi Perform a simulation study using a 'study_parameters'-object
simulate_data Generate a data set using a 'study_parameters'-object
simulate_data.plcp 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
unequal_clusters Setup unbalanced cluster sizes
update.plcp Update a 'study_parameters'-object with new settings