powerNLSEM (version 0.1.2)

plot.powerNLSEM: plot powerNLSEM object

Description

plot powerNLSEM object

Usage

# S3 method for powerNLSEM
plot(
  x,
  test = NULL,
  plot = "power_model",
  power_modeling_method = NULL,
  se = FALSE,
  power_aim = NULL,
  alpha = NULL,
  alpha_power_modeling = NULL,
  min_num_bins = 10,
  defaultgg = FALSE,
  ...
)

Value

Returns ggplot object of the type specified in plot.

Arguments

x

object of class powerNLSEM

test

Should the parameter be tested with a directed hypothesis (onesided) or with an undirected hypothesis (twosided, also equivalent to Wald-Test for single parameter). Default to NULL, then the same as in fitted powerNLSEM object in x is used.

plot

Character indicating what type of plot to create. Default to "power_model", referencing to the prediction of significant parameters using the model specified in power_modeling_method.

power_modeling_method

Character indicating the power modeling method used. This is only relevant when plot = "power_model" is used. Default to NULL, indicating to use the same power modeling method as was used in the powerNLSEM function.

se

Logical indicating to use confidence intervals based on normal approximation using the standard errors. Default to FALSE.

power_aim

Power level to be included into the plot with respective N. If NULL the same power level as in the powerNLSEM function will be used. If set to 0 no power level and corresponding N will be plotted. Default to NULL, indicating to use the same power modeling method as was used in the powerNLSEM function.

alpha

Alpha value used for confidence intervals, when se = TRUE. Default to NULL, indicating to use the same alpha as was used in the powerNLSEM function. This does not influence the significance decision, although same alpha is used per default.

alpha_power_modeling

Type I-error rate for confidence band around predicted power rate. Used to ensure that the computed N keeps the desired power value (with the given Type I-error rate alpha_power_modeling divided by 2). If set to 1, no confidence band is used. Default to .05.

min_num_bins

minimal number of bins used for aggregating results. Default to 10.

defaultgg

Logical to return default ggplot object. Default to FALSE, which returns theme_minimal and other changes in theme.

...

Additional arguments passed on to the plot function.

Examples

# \donttest{
# write model in lavaan syntax
model <- "
# measurement models
          X =~ 1*x1 + 0.8*x2 + 0.7*x3
          Y =~ 1*y1 + 0.85*y2 + 0.78*y3
          Z =~ 1*z1 + 0.9*z2 + 0.6*z3

# structural models
          Y ~ 0.3*X + .2*Z +  .2*X:Z

# residual variances
         Y~~.7975*Y
         X~~1*X
         Z~~1*Z

# covariances
         X~~0.5*Z

# measurement error variances
         x1~~.1*x1
         x2~~.2*x2
         x3~~.3*x3
         z1~~.2*z1
         z2~~.3*z2
         z3~~.4*z3
         y1~~.5*y1
         y2~~.4*y2
         y3~~.3*y3
"
# run model-implied simulation-based power estimation
# for the effects: c("Y~X", "Y~Z", "Y~X:Z")
Result_Power <- powerNLSEM(model = model, POI = c("Y~X", "Y~Z", "Y~X:Z"),
                           method = "UPI", search_method = "adaptive",
                           steps = 10, power_modeling_method = "probit",
                           R = 1000, power_aim = .8, alpha = .05,
                           alpha_power_modeling = .05,
                           CORES = 1, seed = 2024)

Result_Power
plot(Result_Power)
# }