TotalStd {cTMed} | R Documentation |
Standardized Total Effect Matrix Over a Specific Time Interval
Description
This function computes the standardized total effects matrix
over a specific time interval \Delta t
using the first-order stochastic differential equation model's
drift matrix \boldsymbol{\Phi}
and process noise covariance matrix \boldsymbol{\Sigma}
.
Usage
TotalStd(phi, sigma, delta_t)
Arguments
phi |
Numeric matrix.
The drift matrix ( |
sigma |
Numeric matrix.
The process noise covariance matrix ( |
delta_t |
Numeric.
Time interval
( |
Details
The standardized total effect matrix
over a specific time interval \Delta t
is given by
\mathrm{Total}^{\ast}_{\Delta t}
=
\mathbf{S}
\left(
\exp
\left(
\Delta t
\boldsymbol{\Phi}
\right)
\right)
\mathbf{S}^{-1}
where
\boldsymbol{\Phi}
denotes the drift matrix,
\mathbf{S}
a diagonal matrix with model-implied
standard deviations on the diagonals and
\Delta t
the time interval.
Value
Returns an object
of class ctmedeffect
which is a list with the following elements:
- call
Function call.
- args
Function arguments.
- fun
Function used ("TotalStd").
- output
The standardized matrix of total effects.
Author(s)
Ivan Jacob Agaloos Pesigan
References
Bollen, K. A. (1987). Total, direct, and indirect effects in structural equation models. Sociological Methodology, 17, 37. doi:10.2307/271028
Deboeck, P. R., & Preacher, K. J. (2015). No need to be discrete: A method for continuous time mediation analysis. Structural Equation Modeling: A Multidisciplinary Journal, 23 (1), 61–75. doi:10.1080/10705511.2014.973960
Ryan, O., & Hamaker, E. L. (2021). Time to intervene: A continuous-time approach to network analysis and centrality. Psychometrika, 87 (1), 214–252. doi:10.1007/s11336-021-09767-0
See Also
Other Continuous Time Mediation Functions:
BootBeta()
,
BootBetaStd()
,
BootMed()
,
BootMedStd()
,
DeltaBeta()
,
DeltaBetaStd()
,
DeltaIndirectCentral()
,
DeltaMed()
,
DeltaMedStd()
,
DeltaTotalCentral()
,
Direct()
,
DirectStd()
,
ExpCov()
,
ExpMean()
,
Indirect()
,
IndirectCentral()
,
IndirectStd()
,
MCBeta()
,
MCBetaStd()
,
MCIndirectCentral()
,
MCMed()
,
MCMedStd()
,
MCPhi()
,
MCTotalCentral()
,
Med()
,
MedStd()
,
PosteriorBeta()
,
PosteriorIndirectCentral()
,
PosteriorMed()
,
PosteriorTotalCentral()
,
Total()
,
TotalCentral()
,
Trajectory()
Examples
phi <- matrix(
data = c(
-0.357, 0.771, -0.450,
0.0, -0.511, 0.729,
0, 0, -0.693
),
nrow = 3
)
colnames(phi) <- rownames(phi) <- c("x", "m", "y")
sigma <- matrix(
data = c(
0.24455556, 0.02201587, -0.05004762,
0.02201587, 0.07067800, 0.01539456,
-0.05004762, 0.01539456, 0.07553061
),
nrow = 3
)
delta_t <- 1
TotalStd(
phi = phi,
sigma = sigma,
delta_t = delta_t
)