Let the simple mediation model be defined by
the equations
$$Y = \delta_{Y} + \tau^{\prime} X + \beta M + \varepsilon_{Y},$$
and
$$M = \delta_{M} + \alpha X + \varepsilon_{M}.$$
The function generates data from the multivariate normal distribution
using the model-implied mean vector and covariance matrix
of the simple mediation model.
See MASS::mvrnorm() for more details.
Arguments
- n
Positive integer. Sample size.
- tauprime
Numeric. \(\tau^{\prime}\), that is, the slope for \(Y\) regressed on \(X\), adjusting for \(M\).
- beta
Numeric. \(\beta\), that is, the slope for \(Y\) regressed on \(M\), adjusting for \(X\).
- alpha
Numeric vector. Significance level.
- mu
Numeric. Common mean for \(X\), \(M\), and \(Y\), that is, \(\mu_{X} = \mu_{M} = \mu_{Y}\).
- sigmasq
Numeric. Common variance for \(X\), \(M\), and \(Y\), that is, \(\sigma^{2}_{X} = \sigma^{2}_{M} = \sigma^{2}_{Y}\).
References
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Lawrence Erlbaum Associates.
See also
Other Data Generation Functions:
AmputeData(),
ImputeData()