getValuesFloodlight: Internal: Helper for doNonlinearEffectsAnalysis()

In cSEM: Composite-Based Structural Equation Modeling

Internal: Helper for doNonlinearEffectsAnalysis()

Description

Function that calculates the values required for the floodlight analysis, namely 1) partial effect of the independent variable on the dependent variable for each bootstrap run and for the original estimation for each step of the moderator 2) alpha/2 and 1-alpha/2 quantile of the bootstrap estimates.

Usage

getValuesFloodlight(
  .model = NULL,
  .path_coefficients = args_default()$.path_coefficients,
  .dependent = args_default()$.dependent,
  .independent = args_default()$.independent,
  .moderator = args_default()$.moderator,
  .steps_mod = args_default()$.steps_mod,
  .value_independent = args_default()$.value_independent,
  .alpha = args_default()$.alpha
)

Arguments

.model	A model in lavaan model syntax or a cSEMModel list.
.path_coefficients	List. A list that contains the resampled and the original path coefficient estimates. Typically a part of a cSEMResults_resampled object. Defaults to NULL.
.dependent	Character string. The name of the dependent variable.
.independent	Character string. The name of the independent variable.
.moderator	Character string. The name of the moderator variable.
.steps_mod	A numeric vector. Steps used for the moderator variable in calculating the simple effects of an independent variable on the dependent variable. Defaults to NULL.
.value_independent	Integer. Only required for floodlight analysis; The value of the independent variable in case that it appears as a higher-order term.
.alpha	An integer or a numeric vector of significance levels. Defaults to 0.05.

Details

Only variables that comprise the independent variable are taken into account. If it contains a variable other than the independent variable and the moderator the effect is set to zero as the other variables are evaluated at their means (=0), hence the effect is zero.

cSEM documentation built on Nov. 25, 2022, 1:05 a.m.