summary.plcp_multi_sim: Summarize simulations based on a combination of multiple...

In powerlmm: Power Analysis for Longitudinal Multilevel Models

Description

Summarize simulations based on a combination of multiple parameter values

Usage

## S3 method for class 'plcp_multi_sim'
summary(object, para = "time:treatment",
  model = NULL, alpha = 0.05, model_selection = NULL,
  LRT_alpha = 0.1, ...)

Arguments

object	A multiple simulation object created with simulate.plcp_multi
para	The name of the fixed or random effect that should be summarized.
model	Specifies which model that should be summarized. Accepts either a character with the name used in sim_formula_compare, or an integer value.
alpha	Indicates the significance level. Default is 0.05 (two-tailed), one-tailed tests are not yet implemented.
model_selection	Indicates if model selection should be performed. If NULL (default), all models are returned, if FW or BW model selection is performed using LRT, and the result is based on the selected model from each simulation. See summary.plcp_sim for more information.
LRT_alpha	Indicates the alpha level used when comparing models during model selection.
...	Optional arguments.

Value

A list with class plcp_multi_sim_summary. It can be coursed to a data.frame, using as.data.frame. Each row summarizes one of the parameter combinations used in the simulation. In addition to the setup parameter values, it contains the following columns:

• parameter is the name of the coefficient

• M_est is the mean of the estimates taken over all the simulations.

• theta is the population parameter values specified with study_parameters

• M_se is the mean estimated standard error taken over all the simulations.

• SD_est is the empirical standard error; i.e. the standard deviation of the distribution of the generated estimates

• power is the empirical power of the Wald Z test, i.e. the proportion of simulated p-values < alpha

• power_satt is the empirical power of the Wald t test using Satterthwaite's degree of freedom approximation.

• satt_NA is the proportion of Satterthwaite's approximations that failed.

• prop_zero is the proportion of the simulated estimates that are zero; only shown for random effects.

powerlmm documentation built on May 2, 2019, 3:10 a.m.