Summary Method for an Object of Class ctmedmc
Usage
# S3 method for class 'ctmedmc'
summary(object, alpha = 0.05, digits = 4, ...)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)
#> Call:
#> MCMed(phi = phi, vcov_phi_vec = vcov_phi_vec, delta_t = 1, from = "x",
#> to = "y", med = "m", R = 100L)
#>
#> Total, Direct, and Indirect Effects
#>
#> effect interval est se R 2.5% 97.5%
#> 1 total 1 -0.1000 0.0349 100 -0.1728 -0.0344
#> 2 direct 1 -0.2675 0.0454 100 -0.3531 -0.1803
#> 3 indirect 1 0.1674 0.0189 100 0.1310 0.1991
# 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)
#> Call:
#> MCMed(phi = phi, vcov_phi_vec = vcov_phi_vec, delta_t = 1:5,
#> from = "x", to = "y", med = "m", R = 100L)
#>
#> Total, Direct, and Indirect Effects
#>
#> effect interval est se R 2.5% 97.5%
#> 1 total 1 -0.1000 0.0283 100 -0.1523 -0.0412
#> 2 direct 1 -0.2675 0.0379 100 -0.3410 -0.1958
#> 3 indirect 1 0.1674 0.0181 100 0.1303 0.1973
#> 4 total 2 0.0799 0.0318 100 0.0173 0.1382
#> 5 direct 2 -0.3209 0.0533 100 -0.4335 -0.2250
#> 6 indirect 2 0.4008 0.0472 100 0.3209 0.4844
#> 7 total 3 0.2508 0.0341 100 0.1789 0.3160
#> 8 direct 3 -0.2914 0.0600 100 -0.4250 -0.1953
#> 9 indirect 3 0.5423 0.0723 100 0.4313 0.6825
#> 10 total 4 0.3449 0.0396 100 0.2776 0.4253
#> 11 direct 4 -0.2374 0.0614 100 -0.3713 -0.1499
#> 12 indirect 4 0.5823 0.0888 100 0.4543 0.7487
#> 13 total 5 0.3693 0.0454 100 0.3097 0.4771
#> 14 direct 5 -0.1828 0.0592 100 -0.3156 -0.1139
#> 15 indirect 5 0.5521 0.0964 100 0.4232 0.7533