Print the content of the
output of do_boot() or related
functions.
Usage
# S3 method for class 'boot_out'
print(x, ...)Arguments
- x
The output of
do_boot(), or anyboot_out-class object returned by similar functions.- ...
Other arguments. Not used.
Examples
data(data_med_mod_ab1)
dat <- data_med_mod_ab1
lm_m <- lm(m ~ x*w + c1 + c2, dat)
lm_y <- lm(y ~ m*w + x + c1 + c2, dat)
lm_out <- lm2list(lm_m, lm_y)
# In real research, R should be 2000 or even 5000
# In real research, no need to set parallel to FALSE
# In real research, no need to set progress to FALSE
# Progress is displayed by default.
lm_boot_out <- do_boot(lm_out, R = 100,
seed = 1234,
progress = FALSE,
parallel = FALSE)
# Print the output of do_boot()
lm_boot_out
#>
#> == A 'boot_out' class object ==
#>
#> Number of bootstrap samples: 100
#> Number of cases in each bootstrap sample: 100
#> (Missing data, if any, is ignored in the count.)
#> Column names in data:
#> [1] m x w c1 c2 x:w y m:w
#> (Note: May contain derived terms such as product terms.)
#>
library(lavaan)
data(data_med_mod_ab1)
dat <- data_med_mod_ab1
dat$"x:w" <- dat$x * dat$w
dat$"m:w" <- dat$m * dat$w
mod <-
"
m ~ x + w + x:w + c1 + c2
y ~ m + w + m:w + x + c1 + c2
"
fit <- sem(model = mod, data = dat, fixed.x = FALSE,
se = "none", baseline = FALSE)
# In real research, R should be 2000 or even 5000
# In real research, no need to set progress to FALSE
# In real research, no need to set parallel to FALSE
# Progress is displayed by default.
fit_boot_out <- do_boot(fit = fit,
R = 40,
seed = 1234,
parallel = FALSE,
progress = FALSE)
# Print the output of do_boot()
fit_boot_out
#>
#> == A 'boot_out' class object ==
#>
#> Number of bootstrap samples: 40
#> Column names in data:
#> [1] m y m:w x w x:w c1 c2
#> (Note: May contain derived terms such as product terms.)
#>