Deal with missing values

[mattansb]

Following #119 - this provides two solutions to missing values:

1. Mean impute them (default)
2. Allow users to pass the data= argument

library(semTools)
library(emmeans)


data("mtcars")
raw_mtcars <- mtcars
mtcars$hp[1] <- NA
model <- " mpg ~ hp + drat + hp:drat "
fit <- sem(model, mtcars, missing = "fiml.x")




ref_grid(fit, lavaan.DV = "mpg")
#> Warning: 'data' contains missing value. Mean-imputing them.
#> 'emmGrid' object with variables:
#>     hp = 147.87
#>     drat = 3.5966


ref_grid(fit, lavaan.DV = "mpg",
         data = raw_mtcars)
#> 'emmGrid' object with variables:
#>     hp = 146.69
#>     drat = 3.5966

emtrends(fit, ~ drat, var = "hp", lavaan.DV = "mpg",
         data = raw_mtcars)
#>  drat hp.trend      SE  df asymp.LCL asymp.UCL
#>   3.6  -0.0506 0.00899 Inf   -0.0682    -0.033
#> 
#> Confidence level used: 0.95

^{Created on 2025-02-10 with reprex v2.1.1}