mmLSTrf_exampledata: Dataset mmLSTrf_exampledata.

In amayer2010/lsttheory: Latent State-Trait Theory

Dataset mmLSTrf_exampledata.

Description

A simulated dataset illustrating data for a study design with 2 fixed situations, 3 measurement occasions, 2 methods and 3 indicators.

Format

A data frame with 500 rows and 36 variables

Details

The variables are named after the following format: Y_{imts} (i = indicator, m = method, t = occasion, s = fixed situation)

• Y_{1111}

• Y_{2111}

• Y_{3111}

• Y_{1211}

• Y_{2211}

• ...

• Y_{2132}

• Y_{3132}

• Y_{1132}

• Y_{2232}

• Y_{3232}

This format reflects the order of indicator variables in a path diagram, where indicators are first grouped by fixed situations, within those they are then grouped by occasions and within those they are lastly grouped by methods. The resulting nested structure has indicators nested within methods, nested within occasions, nested within fixed situations.

The specified population values underlying the simulated data are:

• E(T_{111}) = 2.90

• Comm(T_{112}) = 0.74

• E(T_{112}) = 3.50

• \epsilon_{imts} = 0.15

• Var(T_{111}) = 0.40

• \alpha_{ims} = 0.00

• Var(T_{112}) = 0.98

• \lambda_{ims} = 1.00

• Var(O_{11t1}) = 0.20

• \delta_{ims} = 1.00

• Var(O_{11t2}) = 0.35

• \gamma_{ims} = 1.00

• Var(TM_{ims}) = 0.10

• \beta_{1112} = 0.35

• Var(OM_{mts}) = 0.10

• \beta_{0112} = -0.21

• Var(\omega_{11s}) = 0.20

Trait factors are essentially parallel, other latent variables are essentially equivalent. Scalar MI holds across fixed situations and methods. Latent variables are orthogonal apart from trait factors.

amayer2010/lsttheory documentation built on March 1, 2025, 11:30 a.m.