Print a 'md_semfindr' Class Object

Print the content of a 'md_semfindr'-class object.

Usage

# S3 method for md_semfindr
print(x, digits = 3, first = 10, sort = TRUE, decreasing = TRUE, ...)

Arguments

x

An 'md_semfindr'-class object.

digits

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

first

Numeric. If not NULL, it prints only the first k cases, k equal to first. Default is 10.

sort

Logical. If TRUE, the default, the cases will be sorted based on Mahalanobis distance. The order is determined by decreasing.

decreasing

Logical. Whether cases, if sorted, is on decreasing order. Default is TRUE.

...

Other arguments. They will be ignored.

Value

x is returned invisibly. Called for its side effect.

Details

The print method for the 'md_semfindr'-class object, returned by mahalanobis_rerun() or mahalanobis_predictors(). This method will print the output with the option to sort the cases.

See also

mahalanobis_rerun(), mahalanobis_predictors()

Examples

library(lavaan)
dat <- pa_dat
# The model
mod <-
"
m1 ~ a1 * iv1 + a2 * iv2
dv ~ b * m1
"
# Fit the model
fit <- lavaan::sem(mod, dat)
summary(fit)
#> lavaan 0.6.17 ended normally after 1 iteration
#> 
#>   Estimator                                         ML
#>   Optimization method                           NLMINB
#>   Number of model parameters                         5
#> 
#>   Number of observations                           100
#> 
#> Model Test User Model:
#>                                                       
#>   Test statistic                                 6.711
#>   Degrees of freedom                                 2
#>   P-value (Chi-square)                           0.035
#> 
#> Parameter Estimates:
#> 
#>   Standard errors                             Standard
#>   Information                                 Expected
#>   Information saturated (h1) model          Structured
#> 
#> Regressions:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>   m1 ~                                                
#>     iv1       (a1)    0.215    0.106    2.036    0.042
#>     iv2       (a2)    0.522    0.099    5.253    0.000
#>   dv ~                                                
#>     m1         (b)    0.517    0.106    4.895    0.000
#> 
#> Variances:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>    .m1                0.903    0.128    7.071    0.000
#>    .dv                1.321    0.187    7.071    0.000
#> 
# Fit the model n times. Each time with one case removed.
# For illustration, do this only for selected cases.
fit_rerun <- lavaan_rerun(fit, parallel = FALSE,
                          to_rerun = 1:10)
#> The expected CPU time is 0.37 second(s).
#> Could be faster if run in parallel.
# Compute the Mahalanobis distance for each case
out <- mahalanobis_rerun(fit_rerun)
out
#> 
#> -- Mahalanobis Distance --
#> 
#>       md
#> 9  5.304
#> 7  4.017
#> 3  3.787
#> 10 3.104
#> 8  3.005
#> 5  1.980
#> 1  1.911
#> 4  1.065
#> 2  0.444
#> 6  0.288
#> 
#> Note:
#> - All stored cases are displayed.
#> - Cases sorted by Mahalanobis distance in decreasing order.
print(out, first = 3)
#> 
#> -- Mahalanobis Distance --
#> 
#>      md
#> 9 5.304
#> 7 4.017
#> 3 3.787
#> 
#> Note:
#> - Only the first 3 case(s) is/are displayed. Set ‘first’ to NULL to display all cases.
#> - Cases sorted by Mahalanobis distance in decreasing order.