Helper functions for taking output from generateParams helpers to write population model script using lavaan notation

Helper functions for taking output from generateParams helpers to write population model script using lavaan notation

Usage

scriptPopModAPIM(popModList, ...)

scriptPopModCFM(popModList)

Arguments

popModList

list with necessary parameter options for a given popMod

...

arguments to pass onto helper functions (e.g., saveParamDf)

Value

a lavaan script with parameter values for a latent APIM

See also

Other helpers: generateParams, getOutput, saveParamDf

Examples

popModList.apim <- list(nItemsX = 5,
loadValuesX_A = "moderate", loadValuesX_B = "moderate",
residCorrValuesX = "moderate", iccX = "weak",
nItemsY = 5,
loadValuesY_A = "weak", loadValuesY_B = "mixed",
residCorrValuesY = "mixed", iccY = "strong",
actorA = "moderate", actorB = "very strong",
partnerA = "weak", partnerB = "weak")

scriptPopModAPIM(popModList = popModList.apim, paramType = "structural")
#> $popModScript
#> [1] "#Measurement Model\n\n## Loadings\nX_A =~ 0.55*X_A1 + 0.58*X_A2 + 0.64*X_A3 + 0.62*X_A4 + 0.59*X_A5\nX_B =~ 0.56*X_B1 + 0.66*X_B2 + 0.61*X_B3 + 0.69*X_B4 + 0.51*X_B5\nY_A =~ 0.31*Y_A1 + 0.44*Y_A2 + 0.38*Y_A3 + 0.48*Y_A4 + 0.49*Y_A5\nY_B =~ 0.62*Y_B1 + 0.52*Y_B2 + 0.69*Y_B3 + 0.52*Y_B4 + 0.87*Y_B5\n\n## Uniquenesses\nX_A1 ~~ 0.6975*X_A1\nX_A2 ~~ 0.6636*X_A2\nX_A3 ~~ 0.5904*X_A3\nX_A4 ~~ 0.6156*X_A4\nX_A5 ~~ 0.6519*X_A5\nX_B1 ~~ 0.6864*X_B1\nX_B2 ~~ 0.5644*X_B2\nX_B3 ~~ 0.6279*X_B3\nX_B4 ~~ 0.5239*X_B4\nX_B5 ~~ 0.7399*X_B5\nY_A1 ~~ 0.9039*Y_A1\nY_A2 ~~ 0.8064*Y_A2\nY_A3 ~~ 0.8556*Y_A3\nY_A4 ~~ 0.7696*Y_A4\nY_A5 ~~ 0.7599*Y_A5\nY_B1 ~~ 0.6156*Y_B1\nY_B2 ~~ 0.7296*Y_B2\nY_B3 ~~ 0.5239*Y_B3\nY_B4 ~~ 0.7296*Y_B4\nY_B5 ~~ 0.2431*Y_B5\n\n## Residual Correlations\nX_A1 ~~ 0.14*X_B1\nX_A2 ~~ 0.16*X_B2\nX_A3 ~~ 0.19*X_B3\nX_A4 ~~ 0.17*X_B4\nX_A5 ~~ 0.12*X_B5\nY_A1 ~~ 0.21*Y_B1\nY_A2 ~~ 0.1*Y_B2\nY_A3 ~~ 0.16*Y_B3\nY_A4 ~~ 0.1*Y_B4\nY_A5 ~~ 0.07*Y_B5\n\n# Structural Model\n                        \n## Latent (Co)Variances\nX_A ~~ 1*X_A\nX_B ~~ 1*X_B\nX_A ~~ 0.07*X_B\nY_A ~~ 0.26*Y_B\n\n## Actor and Partner Effects\nY_A ~ 0.12*X_A\nY_B ~ 0.35*X_B\nY_A ~ 0.09*X_B\nY_B ~ 0.07*X_A"
#> 
#> $popModParams
#>   sim_num pop_model samp_model samp_n lhs op   rhs label  est se  z pvalue
#> 1       0    L_APIM         NA     NA  YA  ~    XA    a1 0.12 NA NA     NA
#> 2       0    L_APIM         NA     NA  YB  ~    XB    a2 0.35 NA NA     NA
#> 3       0    L_APIM         NA     NA  YA  ~    XB    p1 0.09 NA NA     NA
#> 4       0    L_APIM         NA     NA  YB  ~    XA    p2 0.07 NA NA     NA
#> 5       0    L_APIM         NA     NA  k1 := p1/a1    k1 0.75 NA NA     NA
#> 6       0    L_APIM         NA     NA  k2 := p2/a2    k2 0.20 NA NA     NA
#>   ci.lower ci.upper std.lv std.all std.nox
#> 1       NA       NA     NA      NA      NA
#> 2       NA       NA     NA      NA      NA
#> 3       NA       NA     NA      NA      NA
#> 4       NA       NA     NA      NA      NA
#> 5       NA       NA     NA      NA      NA
#> 6       NA       NA     NA      NA      NA
#>