Extract relevant regression indices from lavaan model

Extract relevant regression indices from lavaan model through lavaan::parameterEstimates with standardized = TRUE. In this case, the beta (B) represents the resulting std.all column.

Usage

lavaan_reg(fit, nice_table = FALSE, ...)

Arguments

fit: lavaan fit object to extract fit indices from
nice_table: Logical, whether to print the table as a rempsyc::nice_table as well as print the reference values at the bottom of the table.
...: Arguments to be passed to rempsyc::nice_table

Value

A dataframe, including the outcome, predictor, standardized regression coefficient, 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"  
#> 

HS.model <- write_lavaan(latent = latent, regression = regression)
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
#> 

library(lavaan)
fit <- lavaan(HS.model, data=HolzingerSwineford1939,
              auto.var=TRUE, auto.fix.first=TRUE,
              auto.cov.lv.x=TRUE)
lavaan_reg(fit)
#>    Outcome Predictor      B     p
#> 10   ageyr    visual -2.712 0.024
#> 11   ageyr   textual  0.615 0.213
#> 12   ageyr     speed  2.516 0.011
#> 13   grade    visual -2.277 0.012
#> 14   grade   textual  0.888 0.024
#> 15   grade     speed  2.237 0.003