env.two: Simulated two-level dataset

In macc: Mediation Analysis of Causality under Confounding

Description

"env.three" is an R environment containing a data list generated from 50 subjects, and the parameter settings used to generate the data.

Usage

data("env.two")

Format

An R environment.

data2

a list of length 50, each contains a data frame with 3 variables.

Theta

a 2 by 2 matrix, which is the population level model coefficients.

Sigma

the covariance matrix of the model error terms for the single level model.

n

a 50 by 1 matrix, is the number of trials for each subject.

Lambda

the covariance matrix of the model errors in the coefficient regression model.

A

a vector of length 50, is the A value in the single-level for each subject each session.

B

a vector of length 50, is the B value in the single-level for each subject each session.

C

a vector of length 50, is the C value in the single-level for each subject each session.

Details

The number of subjects is N = 50. For each subject, the number of trials is a random draw from a Poisson distribution with mean 100. The population level coefficients are set to be A = 0.5, C = 0.5 and B = -1, and the variances of the model errors are σ_{1_{i}}^2 = 1, σ_{2_{i}}^2 = 4 and the correlation is δ = 0.5. See Section 5.2 of the reference for details. This is a special case of the three-level data with K=1.

References

Zhao, Y., & Luo, X. (2014). Estimating Mediation Effects under Correlated Errors with an Application to fMRI. arXiv preprint arXiv:1410.7217.

Examples

data(env.two)
dt<-get("data2",env.two)

Example output

Loading required package: lme4
Loading required package: Matrix
Loading required package: nlme

Attaching package: 'nlme'

The following object is masked from 'package:lme4':

    lmList

Loading required package: optimx

Attaching package: 'optimx'

The following object is masked from 'package:nlme':

    coef<-

Loading required package: MASS
Loading required package: car

macc documentation built on May 2, 2019, 12:23 p.m.