simslop: Conducts analysis of the simple slopes

Description Usage Arguments Value Helper functions exist Author(s) References

View source: R/simslop.R

Description

The method is an implementation of analysis of the simple slopes as proposed by Preacher, Curran, and Bauer (2006). The default takes parameters needed to conduct analysis of the simple slopes. For objects of class "bootmi.lm", "lm", "lmerMod" and "mira" exist helper functions that extract parameters "coeff", "dat", "cov_matrix" from the object.

Usage

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simslop(object, x_var, m_var, m2_var = NULL, ci = 95,
  mod_values_type = c("sd", "val"), mod_values = c(-1, 1),
  centered = FALSE, dat_org = NULL)

## Default S3 method:
simslop(object, x_var, m_var, m2_var = NULL, ci = 95,
  mod_values_type = c("sd", "val"), mod_values = c(-1, 1),
  centered = FALSE, dat_org = NULL)

## S3 method for class 'lm'
simslop(object, x_var, m_var, m2_var = NULL, ci = 95,
  mod_values_type = c("sd", "val"), mod_values = c(-1, 0, 1),
  centered = FALSE, dat_org = NULL)

## S3 method for class 'mira'
simslop(object, x_var, m_var, m2_var = NULL, ci = 95,
  mod_values_type = c("sd", "val"), mod_values = c(-1, 0, 1),
  centered = FALSE, dat_org = NULL)

## S3 method for class 'lmerMod'
simslop(object, x_var, m_var, m2_var = NULL, ci = 95,
  mod_values_type = c("sd", "val"), mod_values = c(-1, 0, 1),
  centered = FALSE, dat_org = NULL)

Arguments

object

Object containing $coeff, $dat, $cov_matrix

x_var

Name of the independend variable

m_var

Name of the moderating variable

m2_var

Name of optional 2nd moderating variable

ci

Confidence interval, default 95

mod_values_type

Either sd (=standard deviation, default) or val (=values of data used)

mod_values

Vector of values of the moderator, default c(-1,0,1)

centered

Interaction coefficent mean centered? TRUE or FALSE

dat_org

optional original data set used for mira objects, default NULL

Value

object of class "simpleslopes"

Helper functions exist

Uses object to extract coefficients, data, dependend variable and variance covariance matrix

Author(s)

Stephan Volpers stephan.volpers@plixed.de

References

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J. (2006): Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis. In: Journal of Educational and Behavioral Statistics 31 (4), S. 437-448.


svolpers/bootmi documentation built on June 23, 2021, 6:36 a.m.