summary.powerNLSEM: Summary function for powerNLSEM objects

In powerNLSEM: Simulation-Based Power Estimation (MSPE) for Nonlinear SEM

Summary function for powerNLSEM objects

Description

Summary function for powerNLSEM objects

Usage

## S3 method for class 'powerNLSEM'
summary(object, test = NULL, alpha = NULL, ...)

Arguments

object	Result of powerNLSEM function estimating the MSPE. object must be 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 (if NULL, test of the original MSPE is used).
alpha	Type I-error rate for significance decision. Default to NULL (if NULL, alpha of the original MSPE is used).
...	Further arguments to use in summary.

Value

summary of powerNLSEM object

Examples

# 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
summary(Result_Power)

powerNLSEM documentation built on Sept. 27, 2024, 5:10 p.m.