Summary Method for wtna_boot_mixed
Usage
# S3 method for class 'wtna_boot_mixed'
summary(object, ...)Examples
# \donttest{
set.seed(1)
oh <- data.frame(
A = c(1,0,1,0,1,0,1,0),
B = c(0,1,0,1,0,1,0,1),
C = c(1,1,0,0,1,1,0,0)
)
mixed <- wtna(oh, method = "both")
boot <- bootstrap_network(mixed, iter = 20)
summary(boot)
#> $transition
#> from to weight mean sd p_value sig ci_lower ci_upper cr_lower
#> 1 A B 4 1.65 0.6708204 0.9523810 FALSE 0.475 2.525 3.00
#> 2 A C 2 1.65 1.2680279 0.7619048 FALSE 0.000 4.000 1.50
#> 3 B A 3 1.50 0.6882472 0.9523810 FALSE 0.475 2.525 2.25
#> 4 B C 1 1.95 1.2763022 0.6666667 FALSE 0.475 4.575 0.75
#> 5 C A 2 1.65 1.4608937 0.8571429 FALSE 0.000 4.525 1.50
#> 6 C B 2 2.20 1.3218806 0.5714286 FALSE 0.000 4.525 1.50
#> 7 C C 2 2.00 2.0000000 0.8095238 FALSE 0.000 6.525 1.50
#> cr_upper
#> 1 5.00
#> 2 2.50
#> 3 3.75
#> 4 1.25
#> 5 2.50
#> 6 2.50
#> 7 2.50
#>
#> $cooccurrence
#> from to weight mean sd p_value sig ci_lower ci_upper cr_lower
#> 1 A A 4 4.15 1.531253 0.3333333 FALSE 1.475 6.525 3.0
#> 2 A C 2 2.40 1.142481 0.6666667 FALSE 1.000 4.000 1.5
#> 3 B B 4 3.85 1.531253 0.3333333 FALSE 1.475 6.525 3.0
#> 4 B C 2 1.90 1.333772 0.8571429 FALSE 0.000 4.525 1.5
#> 5 C C 4 4.30 1.380313 0.3809524 FALSE 2.000 6.000 3.0
#> cr_upper
#> 1 5.0
#> 2 2.5
#> 3 5.0
#> 4 2.5
#> 5 5.0
#>
# }