Print a 'sbt_ustd_boot' Object

Print method for a 'sbt_ustd_boot' object, which is the output of parameterEstimates_boot().

Usage

# S3 method for class 'sbt_ustd_boot'
print(
  x,
  ...,
  nd = 3,
  output = c("lavaan.printer", "text", "table"),
  drop_cols = "Z"
)

Arguments

x

Object of the class sbt_ustd_boot, the output of parameterEstimates_boot().

...

Optional arguments to be passed to print() methods.

nd

The number of digits after the decimal place. Default is 3.

output

String. How the results are printed. If set to "table", the results are printed in a table format similar to that of lavaan::parameterEstimates(). If set to "text", the results will be printed in a text format similar to the printout of the output of summary() of a 'lavaan'-class object. If set to "lavaan.printer", the default, lavaan.printer will be used to print a more compact version of the "text" output.

drop_cols

The name(s) of the column(s) to drop if output format is "lavaan.printer". Default is "Z", to fit the print out to the usual screen width of 80.

Value

x is returned invisibly. Called for its side effect.

Details

The default format of the printout, "lavaan.printer", is a compact version of the lavaan-style printout, generated by lavaan.printer. Alternatively, users can request a format similar to that of the printout of the summary of a lavaan output by setting output to "text". This format can be used if "lavaan.printer" failed.

Users can also print the content just as a data frame by setting output to "table". Not easy to read much more compact.

See also

parameterEstimates_boot()

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Examples

library(lavaan)
set.seed(5478374)
n <- 50
x <- runif(n) - .5
m <- .40 * x + rnorm(n, 0, sqrt(1 - .40))
y <- .30 * m + rnorm(n, 0, sqrt(1 - .30))
dat <- data.frame(x = x, y = y, m = m)
model <-
'
m ~ a*x
y ~ b*m
ab := a*b
'

# Should set bootstrap to at least 2000 in real studies
fit <- sem(model, data = dat, fixed.x = FALSE)

fit <- store_boot(fit,
                  do_bootstrapping = TRUE,
                  R = 100,
                  iseed = 1234)

est <- parameterEstimates_boot(fit)
#> Warning: The number of bootstrap samples (100) is less than 'boot_pvalue_min_size' (1000). Bootstrap p-values are not computed.
est
#> 
#> Bootstrapping:
#>                                     
#>  Valid Bootstrap Samples: 100       
#>  Level of Confidence:     95.0%     
#>  CI Type:                 Percentile
#> 
#> Parameter Estimates Settings:
#>                                              
#>  Standard errors:                  Standard  
#>  Information:                      Expected  
#>  Information saturated (h1) model: Structured
#> 
#> Regressions:
#>          Estimate    SE     p  CI.Lo CI.Up   bSE bCI.Lo bCI.Up
#>  m ~                                                          
#>   x (a)     0.569 0.343 0.097 -0.103 1.240 0.326 -0.054  1.276
#>  y ~                                                          
#>   m (b)     0.219 0.153 0.153 -0.081 0.519 0.151 -0.060  0.572
#> 
#> Variances:
#>          Estimate    SE     p  CI.Lo CI.Up   bSE bCI.Lo bCI.Up
#>   .m        0.460 0.092 0.000  0.280 0.641 0.093  0.248  0.673
#>   .y        0.570 0.114 0.000  0.347 0.794 0.104  0.386  0.806
#>    x        0.078 0.016 0.000  0.048 0.109 0.012  0.052  0.106
#> 
#> Defined Parameters:
#>          Estimate    SE     p  CI.Lo CI.Up   bSE bCI.Lo bCI.Up
#>  ab (ab)    0.125 0.115 0.279 -0.101 0.350 0.135 -0.027  0.446
#> 
#> Footnote:
#> - SE: Original standard errors.
#> - p: Original p-values.
#> - CI.Lo, CI.Up: Original confidence intervals.
#> - bSE: Bootstrap standard errors.
#> - bCI.Lo, bCI.Up: Bootstrap confidence intervals.