mediate_ws: Calculate indirect effects of X on Y through a mediator in...

In robinsones/rmemore: Calculates Indirect Effect of Independent Variable on Dependent Variable through a Mediator in Two-Condition Within Subjects Design

Description

Calculate indirect effects of X on Y through a mediator in two-condition within-subjects design

Usage

tidy.bootci(x, estimate = FALSE)

mediate_ws(df, M1, M2, Y1, Y2, Reps = 5000, CONF = 0.95, BSType = "basic")

Arguments

df	a tidy dataframe, each row one observation and with columns for that have the value for the mediating variable at time 1, the mediating variable at time 2, the value of the dependent variable (Y) at time 1, and the value of the dependent variable at time 2, respectively
M1	the name of the column with the values of the mediating variable at time 1
M2	the name of the column with the values of the mediating variable at time 2
Y1	the name of the column with the values of the dependent variable at time 1
Y2	the name of the column with teh values of the dependent variable at time2
Reps	the number of bootstrap samples
CONF	the confidence interval width. You can have multiple values here.
BSType	the bootstrap CI that is calculated

Value

A data frame, where each row is a different bootstrap calculation (if you did more than one). There is a column indicating the bootstrap method used, the confidence interval level, the lower bound of the confidence interval, the higher bound of the confidence interval, and the estimate

Examples

mediate_ws(sample_data, M1, M2, Y1, Y2, Reps = 3000, CONF = c(.9, .95, .99), BSType = "bca")

robinsones/rmemore documentation built on May 27, 2019, 11:39 a.m.