plot.powRICLPM {powRICLPM}

Plot results from powRICLPM object

Description

Visualizes (using ggplot2) the results from a powRICLPM analysis, for a specific parameter, across all experimental conditions. By default, sample size is plotted on the x-axis, power on the y-axis, and results are grouped by the number of time points and wrapped by the proportion of between-unit variance. Optionally, the y argument can be used to change the variable on the y-axis to other outcomes from the powRICLPM analysis.

Usage

## S3 method for class 'powRICLPM'
plot(x, y = "power", ..., parameter = NULL)

Arguments

x

A powRICLPM object.

y

(optional) A character string, specifying which outcome is plotted on the y-axis (see "Details").

...

(don't use)

parameter

Character string of length denoting the parameter to visualize the results for.

Details

y-axis options

The following outcomes can be plotted on the y-axis:

• average: The average estimate.

• MSE: The mean square error.

• coverage: The coverage rate

• accuracy: The average width of the confidence interval.

• SD: Standard deviation of parameter estimates.

• SEAvg: Average standard error.

• bias: The absolute difference between the average estimate and population value.

Value

A ggplot2 object.

See Also

give: Extract information (e.g., performance measures) for a specific parameter, across all experimental conditions. This function is used internally in plot.powRICLPM.

Examples

# Visualize power for "wB2~wA1" across simulation conditions
plot(out_preliminary, parameter = "wB2~wA1")

# Visualize bias for "wB2~wA1" across simulation conditions
plot(out_preliminary, y = "bias", parameter = "wB2~wA1")

# Visualize coverage rate for "wB2~wA1" across simulation conditions
plot(out_preliminary, y = "coverage", parameter = "wB2~wA1")

# Visualize MSE for autoregressive effect across simulation conditions
plot(out_preliminary, y = "MSE", parameter = "wA2~wA1")

# Error: No parameter specified
try(plot(out_preliminary))