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get_pi_data() is a function for creating a dataset with product indiactors used for estimating latent interaction models using one of the product indicator approaches.

Usage

get_pi_data(model.syntax, data, method = "dblcent", match = FALSE, ...)

Arguments

model.syntax

lavaan syntax

data

data to create product indicators from

method

method to use: "rca" = residual centering approach, "uca" = unconstrained approach, "dblcent" = double centering approach, "pind" = prod ind approach, with no constraints or centering, "custom" = use parameters specified in the function call

match

should the product indicators be created by using the match-strategy

...

arguments passed to other functions (e.g., modsem_pi)

Value

data.frame

Examples

library(modsem)
library(lavaan)
#> This is lavaan 0.6-19
#> lavaan is FREE software! Please report any bugs.
m1 <- '
  # Outer Model
  X =~ x1 + x2 +x3
  Y =~ y1 + y2 + y3
  Z =~ z1 + z2 + z3

  # Inner model
  Y ~ X + Z + X:Z
'
syntax <- get_pi_syntax(m1)
data <- get_pi_data(m1, oneInt)
est <- sem(syntax, data)
summary(est)
#> lavaan 0.6-19 ended normally after 161 iterations
#> 
#>   Estimator                                         ML
#>   Optimization method                           NLMINB
#>   Number of model parameters                        60
#> 
#>   Number of observations                          2000
#> 
#> Model Test User Model:
#>                                                       
#>   Test statistic                               122.924
#>   Degrees of freedom                               111
#>   P-value (Chi-square)                           0.207
#> 
#> Parameter Estimates:
#> 
#>   Standard errors                             Standard
#>   Information                                 Expected
#>   Information saturated (h1) model          Structured
#> 
#> Latent Variables:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>   X =~                                                
#>     x1                1.000                           
#>     x2                0.804    0.013   63.612    0.000
#>     x3                0.916    0.014   67.144    0.000
#>   Y =~                                                
#>     y1                1.000                           
#>     y2                0.798    0.007  107.428    0.000
#>     y3                0.899    0.008  112.453    0.000
#>   Z =~                                                
#>     z1                1.000                           
#>     z2                0.812    0.013   64.763    0.000
#>     z3                0.882    0.013   67.014    0.000
#>   XZ =~                                               
#>     x1z1              1.000                           
#>     x2z1              0.805    0.013   60.636    0.000
#>     x3z1              0.877    0.014   62.680    0.000
#>     x1z2              0.793    0.013   59.343    0.000
#>     x2z2              0.646    0.015   43.672    0.000
#>     x3z2              0.706    0.016   44.292    0.000
#>     x1z3              0.887    0.014   63.700    0.000
#>     x2z3              0.716    0.016   45.645    0.000
#>     x3z3              0.781    0.017   45.339    0.000
#> 
#> Regressions:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>   Y ~                                                 
#>     X                 0.675    0.027   25.379    0.000
#>     Z                 0.561    0.026   21.606    0.000
#>     XZ                0.702    0.027   26.360    0.000
#> 
#> Covariances:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>  .x1z1 ~~                                             
#>    .x1z2              0.115    0.008   14.802    0.000
#>    .x1z3              0.114    0.008   13.947    0.000
#>    .x2z1              0.125    0.008   16.095    0.000
#>    .x3z1              0.140    0.009   16.135    0.000
#>  .x1z2 ~~                                             
#>    .x1z3              0.103    0.007   14.675    0.000
#>    .x2z2              0.128    0.006   20.850    0.000
#>    .x3z2              0.146    0.007   21.243    0.000
#>  .x1z3 ~~                                             
#>    .x2z3              0.116    0.007   17.818    0.000
#>    .x3z3              0.135    0.007   18.335    0.000
#>  .x2z1 ~~                                             
#>    .x2z2              0.135    0.006   20.905    0.000
#>    .x2z3              0.145    0.007   21.145    0.000
#>    .x3z1              0.114    0.007   16.058    0.000
#>  .x2z2 ~~                                             
#>    .x2z3              0.117    0.006   20.419    0.000
#>    .x3z2              0.116    0.006   20.586    0.000
#>  .x2z3 ~~                                             
#>    .x3z3              0.109    0.006   18.059    0.000
#>  .x3z1 ~~                                             
#>    .x3z2              0.138    0.007   19.331    0.000
#>    .x3z3              0.158    0.008   20.269    0.000
#>  .x3z2 ~~                                             
#>    .x3z3              0.131    0.007   19.958    0.000
#>   X ~~                                                
#>     Z                 0.201    0.024    8.271    0.000
#>     XZ                0.016    0.025    0.628    0.530
#>   Z ~~                                                
#>     XZ                0.062    0.025    2.449    0.014
#> 
#> Variances:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>    .x1                0.160    0.009   17.871    0.000
#>    .x2                0.162    0.007   22.969    0.000
#>    .x3                0.163    0.008   20.161    0.000
#>    .y1                0.159    0.009   17.896    0.000
#>    .y2                0.154    0.007   22.640    0.000
#>    .y3                0.164    0.008   20.698    0.000
#>    .z1                0.168    0.009   18.143    0.000
#>    .z2                0.158    0.007   22.264    0.000
#>    .z3                0.158    0.008   20.389    0.000
#>    .x1z1              0.311    0.014   22.227    0.000
#>    .x2z1              0.292    0.011   27.287    0.000
#>    .x3z1              0.327    0.012   26.275    0.000
#>    .x1z2              0.290    0.011   26.910    0.000
#>    .x2z2              0.239    0.008   29.770    0.000
#>    .x3z2              0.270    0.009   29.117    0.000
#>    .x1z3              0.272    0.012   23.586    0.000
#>    .x2z3              0.245    0.009   27.979    0.000
#>    .x3z3              0.297    0.011   28.154    0.000
#>     X                 0.981    0.036   26.895    0.000
#>    .Y                 0.990    0.038   25.926    0.000
#>     Z                 1.016    0.038   26.856    0.000
#>     XZ                1.045    0.044   24.004    0.000
#>