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(
0.002704274, -0.001475275, 0.000949122,
-0.001619422, 0.000885122, -0.000569404,
0.00085493, -0.000465824, 0.000297815,
-0.001475275, 0.004428442, -0.002642303,
0.000980573, -0.00271817, 0.001618805,
-0.000586921, 0.001478421, -0.000871547,
0.000949122, -0.002642303, 0.006402668,
-0.000697798, 0.001813471, -0.004043138,
0.000463086, -0.001120949, 0.002271711,
-0.001619422, 0.000980573, -0.000697798,
0.002079286, -0.001152501, 0.000753,
-0.001528701, 0.000820587, -0.000517524,
0.000885122, -0.00271817, 0.001813471,
-0.001152501, 0.00342605, -0.002075005,
0.000899165, -0.002532849, 0.001475579,
-0.000569404, 0.001618805, -0.004043138,
0.000753, -0.002075005, 0.004984032,
-0.000622255, 0.001634917, -0.003705661,
0.00085493, -0.000586921, 0.000463086,
-0.001528701, 0.000899165, -0.000622255,
0.002060076, -0.001096684, 0.000686386,
-0.000465824, 0.001478421, -0.001120949,
0.000820587, -0.002532849, 0.001634917,
-0.001096684, 0.003328692, -0.001926088,
0.000297815, -0.000871547, 0.002271711,
-0.000517524, 0.001475579, -0.003705661,
0.000686386, -0.001926088, 0.004726235
),
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 0.03423846 100 -0.1666356 -0.04401672
#> 2 direct 1 -0.2674539 0.04395758 100 -0.3567261 -0.18628781
#> 3 indirect 1 0.1674155 0.02013482 100 0.1272750 0.20061066
# 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 0.03395899 100 -0.16476025 -0.0320114
#> 2 direct 1 -0.2674539 0.04709743 100 -0.33969758 -0.1737522
#> 3 indirect 1 0.1674155 0.02007626 100 0.12388402 0.1982442
#> 4 total 2 0.0799008 0.03520320 100 0.01098553 0.1541882
#> 5 direct 2 -0.3209035 0.05552653 100 -0.41779752 -0.2098965
#> 6 indirect 2 0.4008043 0.04125368 100 0.30898862 0.4662702
#> 7 total 3 0.2508138 0.03368900 100 0.18841270 0.3099660
#> 8 direct 3 -0.2914426 0.05239901 100 -0.38632534 -0.1918376
#> 9 indirect 3 0.5422564 0.05233930 100 0.43511469 0.6285914
#> 10 total 4 0.3449279 0.03244313 100 0.28231133 0.3989232
#> 11 direct 4 -0.2373900 0.04644744 100 -0.32719487 -0.1538166
#> 12 indirect 4 0.5823179 0.05746986 100 0.46682812 0.6888180
#> 13 total 5 0.3692538 0.03254938 100 0.30907920 0.4401860
#> 14 direct 5 -0.1828447 0.04019984 100 -0.26357998 -0.1131929
#> 15 indirect 5 0.5520985 0.05939646 100 0.44035670 0.6682153