Print an 'lrtp'- Class Object

Print the content of an lrtp-class object.

Usage

# S3 method for class 'lrtp'
print(
  x,
  digits = 3,
  lrtp_only = TRUE,
  wald_stats = FALSE,
  output = c("text", "data.frame", "table"),
  ...
)

Arguments

x

An lrtp-class object.

digits

Integer. The number of decimal places to print. Default is 3.

lrtp_only

Logical. If TRUE, the default, only parameters with LRT p-values will be printed.

wald_stats

Logical. If TRUE, the usual Wald statistics (e.g., z statistics, p-values, CIs) are printed. FALSE by default, assuming that users prefer using LRT statistics when using lrtp().

output

The format of the printout. If "text", then the style in the summary() of the lavaan-class object is used. If "data.frame" or "table", then the data frame format of lavaan::parameterEstimates() is used.

...

Optional arguments. Not used.

Value

x is returned invisibly. Called for its side effect.

Details

The print method for the output of lrtp().

Additional diagnostic information will be printed if one or more likelihood tests encounter some errors or warnings.

See also

lrtp()

Author

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

Examples

library(lavaan)
data(data_sem16)
mod <-
"
f1 =~ x1 + x2 + x3
f2 =~ x4 + x5 + x6
"
fit <- sem(mod, data_sem16)
#> Warning: lavaan->lavaan():  
#>    the first indicator of the following latent variable(s) is a poor item; 
#>    switching to another marker item (to set the metric) to avoid convergence 
#>    problems; use bad.marker.crit = 0 to switch off this behavior: f2 (x4 -> 
#>    x6)

out <- lrtp(fit)
out
#> 
#> Parameter Estimates:
#> 
#>   Standard errors                             Standard
#>   Information                                 Expected
#>   Information saturated (h1) model          Structured
#> 
#> Covariances:
#>                    Estimate  Std.Err    Chisq     LRTp
#>   f1 ~~                                               
#>     f2                0.134    0.049   10.646    0.001
#> 
print(out, lrtp_only = FALSE)
#> 
#> Parameter Estimates:
#> 
#>   Standard errors                             Standard
#>   Information                                 Expected
#>   Information saturated (h1) model          Structured
#> 
#> Latent Variables:
#>                    Estimate  Std.Err    Chisq     LRTp
#>   f1 =~                                               
#>     x1                1.000                NA       NA
#>     x2                0.963    0.252       NA       NA
#>     x3                1.054    0.284       NA       NA
#>   f2 =~                                               
#>     x4                0.422    0.189       NA       NA
#>     x5                0.748    0.292       NA       NA
#>     x6                1.000                NA       NA
#> 
#> Covariances:
#>                    Estimate  Std.Err    Chisq     LRTp
#>   f1 ~~                                               
#>     f2                0.134    0.049   10.646    0.001
#> 
#> Variances:
#>                    Estimate  Std.Err    Chisq     LRTp
#>    .x1                1.020    0.111       NA       NA
#>    .x2                1.048    0.109       NA       NA
#>    .x3                0.709    0.100       NA       NA
#>    .x4                1.154    0.096       NA       NA
#>    .x5                0.972    0.114       NA       NA
#>    .x6                0.826    0.162       NA       NA
#>     f1                0.276    0.100       NA       NA
#>     f2                0.375    0.163       NA       NA
#>