Summary Method for an Object of Class ctmedmc
Usage
# S3 method for class 'ctmedmc'
summary(object, alpha = 0.05, ...)Value
Returns a data frame of effects, time intervals, estimates, standard errors, number of Monte Carlo replications, and confidence intervals.
Examples
set.seed(42)
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")
vcov_phi_vec <- matrix(
data = c(
0.00843, 0.00040, -0.00151,
-0.00600, -0.00033, 0.00110,
0.00324, 0.00020, -0.00061,
0.00040, 0.00374, 0.00016,
-0.00022, -0.00273, -0.00016,
0.00009, 0.00150, 0.00012,
-0.00151, 0.00016, 0.00389,
0.00103, -0.00007, -0.00283,
-0.00050, 0.00000, 0.00156,
-0.00600, -0.00022, 0.00103,
0.00644, 0.00031, -0.00119,
-0.00374, -0.00021, 0.00070,
-0.00033, -0.00273, -0.00007,
0.00031, 0.00287, 0.00013,
-0.00014, -0.00170, -0.00012,
0.00110, -0.00016, -0.00283,
-0.00119, 0.00013, 0.00297,
0.00063, -0.00004, -0.00177,
0.00324, 0.00009, -0.00050,
-0.00374, -0.00014, 0.00063,
0.00495, 0.00024, -0.00093,
0.00020, 0.00150, 0.00000,
-0.00021, -0.00170, -0.00004,
0.00024, 0.00214, 0.00012,
-0.00061, 0.00012, 0.00156,
0.00070, -0.00012, -0.00177,
-0.00093, 0.00012, 0.00223
),
nrow = 9
)
# Specific time interval ----------------------------------------------------
mc <- MCMed(
phi = phi,
vcov_phi_vec = vcov_phi_vec,
delta_t = 1,
from = "x",
to = "y",
med = "m",
R = 100L # use a large value for R in actual research
)
summary(mc)
#> effect interval est se R 2.5% 97.5%
#> 1 total 1 -0.1000384 0.03485068 100 -0.1727980 -0.03444335
#> 2 direct 1 -0.2674539 0.04544184 100 -0.3530971 -0.18029584
#> 3 indirect 1 0.1674155 0.01890677 100 0.1310468 0.19907046
# Range of time intervals ---------------------------------------------------
mc <- MCMed(
phi = phi,
vcov_phi_vec = vcov_phi_vec,
delta_t = 1:5,
from = "x",
to = "y",
med = "m",
R = 100L # use a large value for R in actual research
)
summary(mc)
#> effect interval est se R 2.5% 97.5%
#> 1 total 1 -0.1000384 0.02828969 100 -0.15232781 -0.04123191
#> 2 direct 1 -0.2674539 0.03785126 100 -0.34098924 -0.19575030
#> 3 indirect 1 0.1674155 0.01813653 100 0.13034214 0.19730024
#> 4 total 2 0.0799008 0.03177536 100 0.01734713 0.13816481
#> 5 direct 2 -0.3209035 0.05331547 100 -0.43347383 -0.22496835
#> 6 indirect 2 0.4008043 0.04715986 100 0.32090375 0.48438931
#> 7 total 3 0.2508138 0.03411898 100 0.17891544 0.31595326
#> 8 direct 3 -0.2914426 0.06004235 100 -0.42496332 -0.19529856
#> 9 indirect 3 0.5422564 0.07226284 100 0.43134204 0.68245524
#> 10 total 4 0.3449279 0.03955381 100 0.27762014 0.42528849
#> 11 direct 4 -0.2373900 0.06142283 100 -0.37132486 -0.14987686
#> 12 indirect 4 0.5823179 0.08884600 100 0.45427525 0.74867661
#> 13 total 5 0.3692538 0.04543535 100 0.30966378 0.47707320
#> 14 direct 5 -0.1828447 0.05923691 100 -0.31560524 -0.11390776
#> 15 indirect 5 0.5520985 0.09636387 100 0.42321469 0.75325267