Simulated data for mediation tutorials

Artificial data used to demonstrate model syntax, estimation, and categorical predictors. The labels do not identify substantive psychological constructs. This is distinct from the empirical manuscript dataset wsmed_examples().

Usage

example_data

Format

A tibble (data frame) with 100 rows and 14 variables:

A1, A2, A3

Numeric measurements for variable A at three conditions.

B1, B2, B3

Numeric measurements for variable B at three conditions.

C1, C2, C3

Numeric measurements for variable C at three conditions.

D1, D2, D3

Numeric measurements for variable D at three conditions.

Group

An unordered factor with levels high, med, and low, in that order.

W_Group

An unordered factor with levels high, med, and low, in that order.

Details

All columns are complete. A wsMed analysis selects two condition columns per outcome or mediator. The factor labels are nominal categories; they do not request an ordinal regression model. Set their level order explicitly before fitting to select a different reference category.

See also

wsmed_examples(), wsmed_categorical

Examples

data(example_data)
dim(example_data)
#> [1] 100  14
levels(example_data$Group)
#> [1] "high" "med"  "low"