Extract relevant covariance indices from lavaan model through
lavaan::parameterEstimates with standardized = TRUE. In this
case, the correlation coefficient (r) represents the resulting
std.all column.
Arguments
- fit
lavaan fit object to extract covariance indices from
- nice_table
Logical, whether to print the table as a
rempsyc::nice_tableas well as print the reference values at the bottom of the table.- ...
Arguments to be passed to
rempsyc::nice_table
Value
A dataframe of covariances, including the covaried variables, the covariance, and corresponding p-value.
Examples
(latent <- list(visual = paste0("x", 1:3),
textual = paste0("x", 4:6),
speed = paste0("x", 7:9)))
#> $visual
#> [1] "x1" "x2" "x3"
#>
#> $textual
#> [1] "x4" "x5" "x6"
#>
#> $speed
#> [1] "x7" "x8" "x9"
#>
(regression <- list(ageyr = c("visual", "textual", "speed"),
grade = c("visual", "textual", "speed")))
#> $ageyr
#> [1] "visual" "textual" "speed"
#>
#> $grade
#> [1] "visual" "textual" "speed"
#>
(covariance <- list(speed = "textual", ageyr = "grade"))
#> $speed
#> [1] "textual"
#>
#> $ageyr
#> [1] "grade"
#>
HS.model <- write_lavaan(regression = regression, covariance = covariance,
latent = latent, label = TRUE)
cat(HS.model)
#> ##################################################
#> # [-----Latent variables (measurement model)-----]
#>
#> visual =~ x1 + x2 + x3
#> textual =~ x4 + x5 + x6
#> speed =~ x7 + x8 + x9
#>
#> ##################################################
#> # [---------Regressions (Direct effects)---------]
#>
#> ageyr ~ visual + textual + speed
#> grade ~ visual + textual + speed
#>
#> ##################################################
#> # [------------------Covariances-----------------]
#>
#> speed ~~ textual
#> ageyr ~~ grade
#>
library(lavaan)
fit <- lavaan(HS.model, data=HolzingerSwineford1939,
auto.var=TRUE, auto.fix.first=TRUE,
auto.cov.lv.x=TRUE)
lavaan_cov(fit)
#> Variable.1 Variable.2 r p
#> 16 textual speed 0.268 0.001
#> 17 ageyr grade 0.533 0.000
#> 18 x1 x1 0.395 0.000
#> 19 x2 x2 0.820 0.000
#> 20 x3 x3 0.667 0.000
#> 21 x4 x4 0.268 0.000
#> 22 x5 x5 0.264 0.000
#> 23 x6 x6 0.311 0.000
#> 24 x7 x7 0.641 0.000
#> 25 x8 x8 0.437 0.000
#> 26 x9 x9 0.610 0.000
#> 27 ageyr ageyr 0.839 0.000
#> 28 grade grade 0.809 0.000
#> 29 visual visual 1.000 0.000
#> 30 textual textual 1.000 0.000
#> 31 speed speed 1.000 0.000
#> 32 visual textual 0.458 0.000
#> 33 visual speed 0.438 0.000