Construct bias corrected means

Goal

Construct bias corrected means to use in the main analyses.

Packages and data import

#library
library(tidyverse)
library(lavaan)
library(data.table)
library(doParallel)
library(parallel)

#load robustness data
load(file = "data/data-processed/ml_sem_data/240823_lisscdn-mlsem-panel-data-sibling-missing.Rdata")

mlsem_datafiles_robustness <- mlsem_datafiles

#load main datafile
load(file = "data/data-processed/ml_sem_data/240816_lisscdn-mlsem-panel-data-cleaned.Rdata")

#set main datafile as MyData
MyData <- mlsem_datafiles[[2]]

Analyses

Create bias corrected means function

This function creates for a dataset the bias corrected means for education, political discussion, newness, and average similarity.

f_bias_corrected_means <- function(x) { #x = MyData
  ## Education
  model_means_educ_a <- '

  #alters are assumed to be identical thus equal loadings, variances and intercepts at each time point

  #constrained loadings
  Feduc_a_1 =~ 1*educ_a.1_1 + 1*educ_a.2_1 + 1*educ_a.3_1 +  1*educ_a.4_1 + 1*educ_a.5_1
  Feduc_a_2 =~ 1*educ_a.1_2 + 1*educ_a.2_2 + 1*educ_a.3_2 +  1*educ_a.4_2 + 1*educ_a.5_2
  Feduc_a_3 =~ 1*educ_a.1_3 + 1*educ_a.2_3 + 1*educ_a.3_3 +  1*educ_a.4_3 + 1*educ_a.5_3
  Feduc_a_4 =~ 1*educ_a.1_4 + 1*educ_a.2_4 + 1*educ_a.3_4 +  1*educ_a.4_4 + 1*educ_a.5_4
  Feduc_a_5 =~ 1*educ_a.1_5 + 1*educ_a.2_5 + 1*educ_a.3_5 +  1*educ_a.4_5 + 1*educ_a.5_5
  Feduc_a_6 =~ 1*educ_a.1_6 + 1*educ_a.2_6 + 1*educ_a.3_6 +  1*educ_a.4_6 + 1*educ_a.5_6
  Feduc_a_7 =~ 1*educ_a.1_7 + 1*educ_a.2_7 + 1*educ_a.3_7 +  1*educ_a.4_7 + 1*educ_a.5_7
  Feduc_a_8 =~ 1*educ_a.1_8 + 1*educ_a.2_8 + 1*educ_a.3_8 +  1*educ_a.4_8 + 1*educ_a.5_8
  Feduc_a_9 =~ 1*educ_a.1_9 + 1*educ_a.2_9 + 1*educ_a.3_9 +  1*educ_a.4_9 + 1*educ_a.5_9
  Feduc_a_10 =~ 1*educ_a.1_10 + 1*educ_a.2_10 + 1*educ_a.3_10 +  1*educ_a.4_10 + 1*educ_a.5_10
  Feduc_a_11 =~ 1*educ_a.1_11 + 1*educ_a.2_11 + 1*educ_a.3_11 +  1*educ_a.4_11 + 1*educ_a.5_11


  Feduc_a_1 ~~ Feduc_a_1
  Feduc_a_2 ~~ Feduc_a_2
  Feduc_a_3 ~~ Feduc_a_3
  Feduc_a_4 ~~ Feduc_a_4
  Feduc_a_5 ~~ Feduc_a_5
  Feduc_a_6 ~~ Feduc_a_6
  Feduc_a_7 ~~ Feduc_a_7
  Feduc_a_8 ~~ Feduc_a_8
  Feduc_a_9 ~~ Feduc_a_9
  Feduc_a_10 ~~ Feduc_a_10
  Feduc_a_11 ~~ Feduc_a_11

  #constrained variances
  educ_a.1_1 ~~ x*educ_a.1_1
  educ_a.2_1 ~~ x*educ_a.2_1
  educ_a.3_1 ~~ x*educ_a.3_1
  educ_a.4_1 ~~ x*educ_a.4_1
  educ_a.5_1 ~~ x*educ_a.5_1

  educ_a.1_2 ~~ z*educ_a.1_2
  educ_a.2_2 ~~ z*educ_a.2_2
  educ_a.3_2 ~~ z*educ_a.3_2
  educ_a.4_2 ~~ z*educ_a.4_2
  educ_a.5_2 ~~ z*educ_a.5_2

  educ_a.1_3 ~~ a*educ_a.1_3
  educ_a.2_3 ~~ a*educ_a.2_3
  educ_a.3_3 ~~ a*educ_a.3_3
  educ_a.4_3 ~~ a*educ_a.4_3
  educ_a.5_3 ~~ a*educ_a.5_3

  educ_a.1_4 ~~ b*educ_a.1_4
  educ_a.2_4 ~~ b*educ_a.2_4
  educ_a.3_4 ~~ b*educ_a.3_4
  educ_a.4_4 ~~ b*educ_a.4_4
  educ_a.5_4 ~~ b*educ_a.5_4

  educ_a.1_5 ~~ c*educ_a.1_5
  educ_a.2_5 ~~ c*educ_a.2_5
  educ_a.3_5 ~~ c*educ_a.3_5
  educ_a.4_5 ~~ c*educ_a.4_5
  educ_a.5_5 ~~ c*educ_a.5_5

  educ_a.1_6 ~~ d*educ_a.1_6
  educ_a.2_6 ~~ d*educ_a.2_6
  educ_a.3_6 ~~ d*educ_a.3_6
  educ_a.4_6 ~~ d*educ_a.4_6
  educ_a.5_6 ~~ d*educ_a.5_6

  educ_a.1_7 ~~ e*educ_a.1_7
  educ_a.2_7 ~~ e*educ_a.2_7
  educ_a.3_7 ~~ e*educ_a.3_7
  educ_a.4_7 ~~ e*educ_a.4_7
  educ_a.5_7 ~~ e*educ_a.5_7

  educ_a.1_8 ~~ f*educ_a.1_8
  educ_a.2_8 ~~ f*educ_a.2_8
  educ_a.3_8 ~~ f*educ_a.3_8
  educ_a.4_8 ~~ f*educ_a.4_8
  educ_a.5_8 ~~ f*educ_a.5_8

  educ_a.1_9 ~~ g*educ_a.1_9
  educ_a.2_9 ~~ g*educ_a.2_9
  educ_a.3_9 ~~ g*educ_a.3_9
  educ_a.4_9 ~~ g*educ_a.4_9
  educ_a.5_9 ~~ g*educ_a.5_9

  educ_a.1_10 ~~ h*educ_a.1_10
  educ_a.2_10 ~~ h*educ_a.2_10
  educ_a.3_10 ~~ h*educ_a.3_10
  educ_a.4_10 ~~ h*educ_a.4_10
  educ_a.5_10 ~~ h*educ_a.5_10

  educ_a.1_11 ~~ i*educ_a.1_11
  educ_a.2_11 ~~ i*educ_a.2_11
  educ_a.3_11 ~~ i*educ_a.3_11
  educ_a.4_11 ~~ i*educ_a.4_11
  educ_a.5_11 ~~ i*educ_a.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  educ_a.1_1 ~ j*1
  educ_a.2_1 ~ j*1
  educ_a.3_1 ~ j*1
  educ_a.4_1 ~ j*1
  educ_a.5_1 ~ j*1

  educ_a.1_2 ~ j*1
  educ_a.2_2 ~ j*1
  educ_a.3_2 ~ j*1
  educ_a.4_2 ~ j*1
  educ_a.5_2 ~ j*1

  educ_a.1_3 ~ j*1
  educ_a.2_3 ~ j*1
  educ_a.3_3 ~ j*1
  educ_a.4_3 ~ j*1
  educ_a.5_3 ~ j*1

  educ_a.1_4 ~ j*1
  educ_a.2_4 ~ j*1
  educ_a.3_4 ~ j*1
  educ_a.4_4 ~ j*1
  educ_a.5_4 ~ j*1

  educ_a.1_5 ~ j*1
  educ_a.2_5 ~ j*1
  educ_a.3_5 ~ j*1
  educ_a.4_5 ~ j*1
  educ_a.5_5 ~ j*1

  educ_a.1_6 ~ j*1
  educ_a.2_6 ~ j*1
  educ_a.3_6 ~ j*1
  educ_a.4_6 ~ j*1
  educ_a.5_6 ~ j*1

  educ_a.1_7 ~ j*1
  educ_a.2_7 ~ j*1
  educ_a.3_7 ~ j*1
  educ_a.4_7 ~ j*1
  educ_a.5_7 ~ j*1

  educ_a.1_8 ~ j*1
  educ_a.2_8 ~ j*1
  educ_a.3_8 ~ j*1
  educ_a.4_8 ~ j*1
  educ_a.5_8 ~ j*1

  educ_a.1_9 ~ j*1
  educ_a.2_9 ~ j*1
  educ_a.3_9 ~ j*1
  educ_a.4_9 ~ j*1
  educ_a.5_9 ~ j*1

  educ_a.1_10 ~ j*1
  educ_a.2_10 ~ j*1
  educ_a.3_10 ~ j*1
  educ_a.4_10 ~ j*1
  educ_a.5_10 ~ j*1

  educ_a.1_11 ~ j*1
  educ_a.2_11 ~ j*1
  educ_a.3_11 ~ j*1
  educ_a.4_11 ~ j*1
  educ_a.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Feduc_a_2 ~ 1
  Feduc_a_3 ~ 1
  Feduc_a_4 ~ 1
  Feduc_a_5 ~ 1
  Feduc_a_6 ~ 1
  Feduc_a_7 ~ 1
  Feduc_a_8 ~ 1
  Feduc_a_9 ~ 1
  Feduc_a_10 ~ 1
  Feduc_a_11 ~ 1


  '
  
  #original education variable
  model_means_educ_orig_a <- '

  #alters are assumed to be identical thus equal loadings, variances and intercepts at each time point

  #constrained loadings
  Feduc_orig_a_1 =~ 1*educ_orig_a.1_1 + 1*educ_orig_a.2_1 + 1*educ_orig_a.3_1 +  1*educ_orig_a.4_1 + 1*educ_orig_a.5_1
  Feduc_orig_a_2 =~ 1*educ_orig_a.1_2 + 1*educ_orig_a.2_2 + 1*educ_orig_a.3_2 +  1*educ_orig_a.4_2 + 1*educ_orig_a.5_2
  Feduc_orig_a_3 =~ 1*educ_orig_a.1_3 + 1*educ_orig_a.2_3 + 1*educ_orig_a.3_3 +  1*educ_orig_a.4_3 + 1*educ_orig_a.5_3
  Feduc_orig_a_4 =~ 1*educ_orig_a.1_4 + 1*educ_orig_a.2_4 + 1*educ_orig_a.3_4 +  1*educ_orig_a.4_4 + 1*educ_orig_a.5_4
  Feduc_orig_a_5 =~ 1*educ_orig_a.1_5 + 1*educ_orig_a.2_5 + 1*educ_orig_a.3_5 +  1*educ_orig_a.4_5 + 1*educ_orig_a.5_5
  Feduc_orig_a_6 =~ 1*educ_orig_a.1_6 + 1*educ_orig_a.2_6 + 1*educ_orig_a.3_6 +  1*educ_orig_a.4_6 + 1*educ_orig_a.5_6
  Feduc_orig_a_7 =~ 1*educ_orig_a.1_7 + 1*educ_orig_a.2_7 + 1*educ_orig_a.3_7 +  1*educ_orig_a.4_7 + 1*educ_orig_a.5_7
  Feduc_orig_a_8 =~ 1*educ_orig_a.1_8 + 1*educ_orig_a.2_8 + 1*educ_orig_a.3_8 +  1*educ_orig_a.4_8 + 1*educ_orig_a.5_8
  Feduc_orig_a_9 =~ 1*educ_orig_a.1_9 + 1*educ_orig_a.2_9 + 1*educ_orig_a.3_9 +  1*educ_orig_a.4_9 + 1*educ_orig_a.5_9
  Feduc_orig_a_10 =~ 1*educ_orig_a.1_10 + 1*educ_orig_a.2_10 + 1*educ_orig_a.3_10 +  1*educ_orig_a.4_10 + 1*educ_orig_a.5_10
  Feduc_orig_a_11 =~ 1*educ_orig_a.1_11 + 1*educ_orig_a.2_11 + 1*educ_orig_a.3_11 +  1*educ_orig_a.4_11 + 1*educ_orig_a.5_11


  Feduc_orig_a_1 ~~ Feduc_orig_a_1
  Feduc_orig_a_2 ~~ Feduc_orig_a_2
  Feduc_orig_a_3 ~~ Feduc_orig_a_3
  Feduc_orig_a_4 ~~ Feduc_orig_a_4
  Feduc_orig_a_5 ~~ Feduc_orig_a_5
  Feduc_orig_a_6 ~~ Feduc_orig_a_6
  Feduc_orig_a_7 ~~ Feduc_orig_a_7
  Feduc_orig_a_8 ~~ Feduc_orig_a_8
  Feduc_orig_a_9 ~~ Feduc_orig_a_9
  Feduc_orig_a_10 ~~ Feduc_orig_a_10
  Feduc_orig_a_11 ~~ Feduc_orig_a_11

  #constrained variances
  educ_orig_a.1_1 ~~ x*educ_orig_a.1_1
  educ_orig_a.2_1 ~~ x*educ_orig_a.2_1
  educ_orig_a.3_1 ~~ x*educ_orig_a.3_1
  educ_orig_a.4_1 ~~ x*educ_orig_a.4_1
  educ_orig_a.5_1 ~~ x*educ_orig_a.5_1

  educ_orig_a.1_2 ~~ z*educ_orig_a.1_2
  educ_orig_a.2_2 ~~ z*educ_orig_a.2_2
  educ_orig_a.3_2 ~~ z*educ_orig_a.3_2
  educ_orig_a.4_2 ~~ z*educ_orig_a.4_2
  educ_orig_a.5_2 ~~ z*educ_orig_a.5_2

  educ_orig_a.1_3 ~~ a*educ_orig_a.1_3
  educ_orig_a.2_3 ~~ a*educ_orig_a.2_3
  educ_orig_a.3_3 ~~ a*educ_orig_a.3_3
  educ_orig_a.4_3 ~~ a*educ_orig_a.4_3
  educ_orig_a.5_3 ~~ a*educ_orig_a.5_3

  educ_orig_a.1_4 ~~ b*educ_orig_a.1_4
  educ_orig_a.2_4 ~~ b*educ_orig_a.2_4
  educ_orig_a.3_4 ~~ b*educ_orig_a.3_4
  educ_orig_a.4_4 ~~ b*educ_orig_a.4_4
  educ_orig_a.5_4 ~~ b*educ_orig_a.5_4

  educ_orig_a.1_5 ~~ c*educ_orig_a.1_5
  educ_orig_a.2_5 ~~ c*educ_orig_a.2_5
  educ_orig_a.3_5 ~~ c*educ_orig_a.3_5
  educ_orig_a.4_5 ~~ c*educ_orig_a.4_5
  educ_orig_a.5_5 ~~ c*educ_orig_a.5_5

  educ_orig_a.1_6 ~~ d*educ_orig_a.1_6
  educ_orig_a.2_6 ~~ d*educ_orig_a.2_6
  educ_orig_a.3_6 ~~ d*educ_orig_a.3_6
  educ_orig_a.4_6 ~~ d*educ_orig_a.4_6
  educ_orig_a.5_6 ~~ d*educ_orig_a.5_6

  educ_orig_a.1_7 ~~ e*educ_orig_a.1_7
  educ_orig_a.2_7 ~~ e*educ_orig_a.2_7
  educ_orig_a.3_7 ~~ e*educ_orig_a.3_7
  educ_orig_a.4_7 ~~ e*educ_orig_a.4_7
  educ_orig_a.5_7 ~~ e*educ_orig_a.5_7

  educ_orig_a.1_8 ~~ f*educ_orig_a.1_8
  educ_orig_a.2_8 ~~ f*educ_orig_a.2_8
  educ_orig_a.3_8 ~~ f*educ_orig_a.3_8
  educ_orig_a.4_8 ~~ f*educ_orig_a.4_8
  educ_orig_a.5_8 ~~ f*educ_orig_a.5_8

  educ_orig_a.1_9 ~~ g*educ_orig_a.1_9
  educ_orig_a.2_9 ~~ g*educ_orig_a.2_9
  educ_orig_a.3_9 ~~ g*educ_orig_a.3_9
  educ_orig_a.4_9 ~~ g*educ_orig_a.4_9
  educ_orig_a.5_9 ~~ g*educ_orig_a.5_9

  educ_orig_a.1_10 ~~ h*educ_orig_a.1_10
  educ_orig_a.2_10 ~~ h*educ_orig_a.2_10
  educ_orig_a.3_10 ~~ h*educ_orig_a.3_10
  educ_orig_a.4_10 ~~ h*educ_orig_a.4_10
  educ_orig_a.5_10 ~~ h*educ_orig_a.5_10

  educ_orig_a.1_11 ~~ i*educ_orig_a.1_11
  educ_orig_a.2_11 ~~ i*educ_orig_a.2_11
  educ_orig_a.3_11 ~~ i*educ_orig_a.3_11
  educ_orig_a.4_11 ~~ i*educ_orig_a.4_11
  educ_orig_a.5_11 ~~ i*educ_orig_a.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  educ_orig_a.1_1 ~ j*1
  educ_orig_a.2_1 ~ j*1
  educ_orig_a.3_1 ~ j*1
  educ_orig_a.4_1 ~ j*1
  educ_orig_a.5_1 ~ j*1

  educ_orig_a.1_2 ~ j*1
  educ_orig_a.2_2 ~ j*1
  educ_orig_a.3_2 ~ j*1
  educ_orig_a.4_2 ~ j*1
  educ_orig_a.5_2 ~ j*1

  educ_orig_a.1_3 ~ j*1
  educ_orig_a.2_3 ~ j*1
  educ_orig_a.3_3 ~ j*1
  educ_orig_a.4_3 ~ j*1
  educ_orig_a.5_3 ~ j*1

  educ_orig_a.1_4 ~ j*1
  educ_orig_a.2_4 ~ j*1
  educ_orig_a.3_4 ~ j*1
  educ_orig_a.4_4 ~ j*1
  educ_orig_a.5_4 ~ j*1

  educ_orig_a.1_5 ~ j*1
  educ_orig_a.2_5 ~ j*1
  educ_orig_a.3_5 ~ j*1
  educ_orig_a.4_5 ~ j*1
  educ_orig_a.5_5 ~ j*1

  educ_orig_a.1_6 ~ j*1
  educ_orig_a.2_6 ~ j*1
  educ_orig_a.3_6 ~ j*1
  educ_orig_a.4_6 ~ j*1
  educ_orig_a.5_6 ~ j*1

  educ_orig_a.1_7 ~ j*1
  educ_orig_a.2_7 ~ j*1
  educ_orig_a.3_7 ~ j*1
  educ_orig_a.4_7 ~ j*1
  educ_orig_a.5_7 ~ j*1

  educ_orig_a.1_8 ~ j*1
  educ_orig_a.2_8 ~ j*1
  educ_orig_a.3_8 ~ j*1
  educ_orig_a.4_8 ~ j*1
  educ_orig_a.5_8 ~ j*1

  educ_orig_a.1_9 ~ j*1
  educ_orig_a.2_9 ~ j*1
  educ_orig_a.3_9 ~ j*1
  educ_orig_a.4_9 ~ j*1
  educ_orig_a.5_9 ~ j*1

  educ_orig_a.1_10 ~ j*1
  educ_orig_a.2_10 ~ j*1
  educ_orig_a.3_10 ~ j*1
  educ_orig_a.4_10 ~ j*1
  educ_orig_a.5_10 ~ j*1

  educ_orig_a.1_11 ~ j*1
  educ_orig_a.2_11 ~ j*1
  educ_orig_a.3_11 ~ j*1
  educ_orig_a.4_11 ~ j*1
  educ_orig_a.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Feduc_orig_a_2 ~ 1
  Feduc_orig_a_3 ~ 1
  Feduc_orig_a_4 ~ 1
  Feduc_orig_a_5 ~ 1
  Feduc_orig_a_6 ~ 1
  Feduc_orig_a_7 ~ 1
  Feduc_orig_a_8 ~ 1
  Feduc_orig_a_9 ~ 1
  Feduc_orig_a_10 ~ 1
  Feduc_orig_a_11 ~ 1


  '
  
  #political discussion
  model_means_pol <- '

  #alters are identical thus equal loadings, variances and intercepts at each time point_

  #constrained loadings
  Fpol_a_1 =~ 1*poltalk_a.1_1 + 1*poltalk_a.2_1 + 1*poltalk_a.3_1 +  1*poltalk_a.4_1 + 1*poltalk_a.5_1
  Fpol_a_2 =~ 1*poltalk_a.1_2 + 1*poltalk_a.2_2 + 1*poltalk_a.3_2 +  1*poltalk_a.4_2 + 1*poltalk_a.5_2
  Fpol_a_3 =~ 1*poltalk_a.1_3 + 1*poltalk_a.2_3 + 1*poltalk_a.3_3 +  1*poltalk_a.4_3 + 1*poltalk_a.5_3
  Fpol_a_4 =~ 1*poltalk_a.1_4 + 1*poltalk_a.2_4 + 1*poltalk_a.3_4 +  1*poltalk_a.4_4 + 1*poltalk_a.5_4
  Fpol_a_5 =~ 1*poltalk_a.1_5 + 1*poltalk_a.2_5 + 1*poltalk_a.3_5 +  1*poltalk_a.4_5 + 1*poltalk_a.5_5
  Fpol_a_6 =~ 1*poltalk_a.1_6 + 1*poltalk_a.2_6 + 1*poltalk_a.3_6 +  1*poltalk_a.4_6 + 1*poltalk_a.5_6
  Fpol_a_7 =~ 1*poltalk_a.1_7 + 1*poltalk_a.2_7 + 1*poltalk_a.3_7 +  1*poltalk_a.4_7 + 1*poltalk_a.5_7
  Fpol_a_8 =~ 1*poltalk_a.1_8 + 1*poltalk_a.2_8 + 1*poltalk_a.3_8 +  1*poltalk_a.4_8 + 1*poltalk_a.5_8
  Fpol_a_9 =~ 1*poltalk_a.1_9 + 1*poltalk_a.2_9 + 1*poltalk_a.3_9 +  1*poltalk_a.4_9 + 1*poltalk_a.5_9
  Fpol_a_10 =~ 1*poltalk_a.1_10 + 1*poltalk_a.2_10 + 1*poltalk_a.3_10 +  1*poltalk_a.4_10 + 1*poltalk_a.5_10
  Fpol_a_11 =~ 1*poltalk_a.1_11 + 1*poltalk_a.2_11 + 1*poltalk_a.3_11 +  1*poltalk_a.4_11 + 1*poltalk_a.5_11


  Fpol_a_1 ~~ Fpol_a_1
  Fpol_a_2 ~~ Fpol_a_2
  Fpol_a_3 ~~ Fpol_a_3
  Fpol_a_4 ~~ Fpol_a_4
  Fpol_a_5 ~~ Fpol_a_5
  Fpol_a_6 ~~ Fpol_a_6
  Fpol_a_7 ~~ Fpol_a_7
  Fpol_a_8 ~~ Fpol_a_8
  Fpol_a_9 ~~ Fpol_a_9
  Fpol_a_10 ~~ Fpol_a_10
  Fpol_a_11 ~~ Fpol_a_11

  #constrained variances
  poltalk_a.1_1 ~~ x*poltalk_a.1_1
  poltalk_a.2_1 ~~ x*poltalk_a.2_1
  poltalk_a.3_1 ~~ x*poltalk_a.3_1
  poltalk_a.4_1 ~~ x*poltalk_a.4_1
  poltalk_a.5_1 ~~ x*poltalk_a.5_1

  poltalk_a.1_2 ~~ z*poltalk_a.1_2
  poltalk_a.2_2 ~~ z*poltalk_a.2_2
  poltalk_a.3_2 ~~ z*poltalk_a.3_2
  poltalk_a.4_2 ~~ z*poltalk_a.4_2
  poltalk_a.5_2 ~~ z*poltalk_a.5_2

  poltalk_a.1_3 ~~ a*poltalk_a.1_3
  poltalk_a.2_3 ~~ a*poltalk_a.2_3
  poltalk_a.3_3 ~~ a*poltalk_a.3_3
  poltalk_a.4_3 ~~ a*poltalk_a.4_3
  poltalk_a.5_3 ~~ a*poltalk_a.5_3

  poltalk_a.1_4 ~~ b*poltalk_a.1_4
  poltalk_a.2_4 ~~ b*poltalk_a.2_4
  poltalk_a.3_4 ~~ b*poltalk_a.3_4
  poltalk_a.4_4 ~~ b*poltalk_a.4_4
  poltalk_a.5_4 ~~ b*poltalk_a.5_4

  poltalk_a.1_5 ~~ c*poltalk_a.1_5
  poltalk_a.2_5 ~~ c*poltalk_a.2_5
  poltalk_a.3_5 ~~ c*poltalk_a.3_5
  poltalk_a.4_5 ~~ c*poltalk_a.4_5
  poltalk_a.5_5 ~~ c*poltalk_a.5_5

  poltalk_a.1_6 ~~ d*poltalk_a.1_6
  poltalk_a.2_6 ~~ d*poltalk_a.2_6
  poltalk_a.3_6 ~~ d*poltalk_a.3_6
  poltalk_a.4_6 ~~ d*poltalk_a.4_6
  poltalk_a.5_6 ~~ d*poltalk_a.5_6

  poltalk_a.1_7 ~~ e*poltalk_a.1_7
  poltalk_a.2_7 ~~ e*poltalk_a.2_7
  poltalk_a.3_7 ~~ e*poltalk_a.3_7
  poltalk_a.4_7 ~~ e*poltalk_a.4_7
  poltalk_a.5_7 ~~ e*poltalk_a.5_7

  poltalk_a.1_8 ~~ f*poltalk_a.1_8
  poltalk_a.2_8 ~~ f*poltalk_a.2_8
  poltalk_a.3_8 ~~ f*poltalk_a.3_8
  poltalk_a.4_8 ~~ f*poltalk_a.4_8
  poltalk_a.5_8 ~~ f*poltalk_a.5_8

  poltalk_a.1_9 ~~ g*poltalk_a.1_9
  poltalk_a.2_9 ~~ g*poltalk_a.2_9
  poltalk_a.3_9 ~~ g*poltalk_a.3_9
  poltalk_a.4_9 ~~ g*poltalk_a.4_9
  poltalk_a.5_9 ~~ g*poltalk_a.5_9

  poltalk_a.1_10 ~~ h*poltalk_a.1_10
  poltalk_a.2_10 ~~ h*poltalk_a.2_10
  poltalk_a.3_10 ~~ h*poltalk_a.3_10
  poltalk_a.4_10 ~~ h*poltalk_a.4_10
  poltalk_a.5_10 ~~ h*poltalk_a.5_10

  poltalk_a.1_11 ~~ i*poltalk_a.1_11
  poltalk_a.2_11 ~~ i*poltalk_a.2_11
  poltalk_a.3_11 ~~ i*poltalk_a.3_11
  poltalk_a.4_11 ~~ i*poltalk_a.4_11
  poltalk_a.5_11 ~~ i*poltalk_a.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  poltalk_a.1_1 ~ j*1
  poltalk_a.2_1 ~ j*1
  poltalk_a.3_1 ~ j*1
  poltalk_a.4_1 ~ j*1
  poltalk_a.5_1 ~ j*1

  poltalk_a.1_2 ~ j*1
  poltalk_a.2_2 ~ j*1
  poltalk_a.3_2 ~ j*1
  poltalk_a.4_2 ~ j*1
  poltalk_a.5_2 ~ j*1

  poltalk_a.1_3 ~ j*1
  poltalk_a.2_3 ~ j*1
  poltalk_a.3_3 ~ j*1
  poltalk_a.4_3 ~ j*1
  poltalk_a.5_3 ~ j*1

  poltalk_a.1_4 ~ j*1
  poltalk_a.2_4 ~ j*1
  poltalk_a.3_4 ~ j*1
  poltalk_a.4_4 ~ j*1
  poltalk_a.5_4 ~ j*1

  poltalk_a.1_5 ~ j*1
  poltalk_a.2_5 ~ j*1
  poltalk_a.3_5 ~ j*1
  poltalk_a.4_5 ~ j*1
  poltalk_a.5_5 ~ j*1

  poltalk_a.1_6 ~ j*1
  poltalk_a.2_6 ~ j*1
  poltalk_a.3_6 ~ j*1
  poltalk_a.4_6 ~ j*1
  poltalk_a.5_6 ~ j*1

  poltalk_a.1_7 ~ j*1
  poltalk_a.2_7 ~ j*1
  poltalk_a.3_7 ~ j*1
  poltalk_a.4_7 ~ j*1
  poltalk_a.5_7 ~ j*1

  poltalk_a.1_8 ~ j*1
  poltalk_a.2_8 ~ j*1
  poltalk_a.3_8 ~ j*1
  poltalk_a.4_8 ~ j*1
  poltalk_a.5_8 ~ j*1

  poltalk_a.1_9 ~ j*1
  poltalk_a.2_9 ~ j*1
  poltalk_a.3_9 ~ j*1
  poltalk_a.4_9 ~ j*1
  poltalk_a.5_9 ~ j*1

  poltalk_a.1_10 ~ j*1
  poltalk_a.2_10 ~ j*1
  poltalk_a.3_10 ~ j*1
  poltalk_a.4_10 ~ j*1
  poltalk_a.5_10 ~ j*1

  poltalk_a.1_11 ~ j*1
  poltalk_a.2_11 ~ j*1
  poltalk_a.3_11 ~ j*1
  poltalk_a.4_11 ~ j*1
  poltalk_a.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Fpol_a_2 ~ 1
  Fpol_a_3 ~ 1
  Fpol_a_4 ~ 1
  Fpol_a_5 ~ 1
  Fpol_a_6 ~ 1
  Fpol_a_7 ~ 1
  Fpol_a_8 ~ 1
  Fpol_a_9 ~ 1
  Fpol_a_10 ~ 1
  Fpol_a_11 ~ 1


  '
  
  #Relationship length (liss variable)
  model_means_length <- '

  #alters are identical thus equal loadings, variances and intercepts at each time point_

  #constrained loadings
  Flength_a_2 =~ 1*length_a.1_2 + 1*length_a.2_2 + 1*length_a.3_2 +  1*length_a.4_2 + 1*length_a.5_2
  Flength_a_3 =~ 1*length_a.1_3 + 1*length_a.2_3 + 1*length_a.3_3 +  1*length_a.4_3 + 1*length_a.5_3
  Flength_a_4 =~ 1*length_a.1_4 + 1*length_a.2_4 + 1*length_a.3_4 +  1*length_a.4_4 + 1*length_a.5_4
  Flength_a_5 =~ 1*length_a.1_5 + 1*length_a.2_5 + 1*length_a.3_5 +  1*length_a.4_5 + 1*length_a.5_5
  Flength_a_6 =~ 1*length_a.1_6 + 1*length_a.2_6 + 1*length_a.3_6 +  1*length_a.4_6 + 1*length_a.5_6
  Flength_a_7 =~ 1*length_a.1_7 + 1*length_a.2_7 + 1*length_a.3_7 +  1*length_a.4_7 + 1*length_a.5_7
  Flength_a_8 =~ 1*length_a.1_8 + 1*length_a.2_8 + 1*length_a.3_8 +  1*length_a.4_8 + 1*length_a.5_8
  Flength_a_9 =~ 1*length_a.1_9 + 1*length_a.2_9 + 1*length_a.3_9 +  1*length_a.4_9 + 1*length_a.5_9
  Flength_a_10 =~ 1*length_a.1_10 + 1*length_a.2_10 + 1*length_a.3_10 +  1*length_a.4_10 + 1*length_a.5_10
  Flength_a_11 =~ 1*length_a.1_11 + 1*length_a.2_11 + 1*length_a.3_11 +  1*length_a.4_11 + 1*length_a.5_11

  Flength_a_2 ~~ Flength_a_2
  Flength_a_3 ~~ Flength_a_3
  Flength_a_4 ~~ Flength_a_4
  Flength_a_5 ~~ Flength_a_5
  Flength_a_6 ~~ Flength_a_6
  Flength_a_7 ~~ Flength_a_7
  Flength_a_8 ~~ Flength_a_8
  Flength_a_9 ~~ Flength_a_9
  Flength_a_10 ~~ Flength_a_10
  Flength_a_11 ~~ Flength_a_11

  #constrained variances
  length_a.1_2 ~~ x*length_a.1_2
  length_a.2_2 ~~ x*length_a.2_2
  length_a.3_2 ~~ x*length_a.3_2
  length_a.4_2 ~~ x*length_a.4_2
  length_a.5_2 ~~ x*length_a.5_2

  length_a.1_3 ~~ a*length_a.1_3
  length_a.2_3 ~~ a*length_a.2_3
  length_a.3_3 ~~ a*length_a.3_3
  length_a.4_3 ~~ a*length_a.4_3
  length_a.5_3 ~~ a*length_a.5_3

  length_a.1_4 ~~ b*length_a.1_4
  length_a.2_4 ~~ b*length_a.2_4
  length_a.3_4 ~~ b*length_a.3_4
  length_a.4_4 ~~ b*length_a.4_4
  length_a.5_4 ~~ b*length_a.5_4

  length_a.1_5 ~~ c*length_a.1_5
  length_a.2_5 ~~ c*length_a.2_5
  length_a.3_5 ~~ c*length_a.3_5
  length_a.4_5 ~~ c*length_a.4_5
  length_a.5_5 ~~ c*length_a.5_5

  length_a.1_6 ~~ d*length_a.1_6
  length_a.2_6 ~~ d*length_a.2_6
  length_a.3_6 ~~ d*length_a.3_6
  length_a.4_6 ~~ d*length_a.4_6
  length_a.5_6 ~~ d*length_a.5_6

  length_a.1_7 ~~ e*length_a.1_7
  length_a.2_7 ~~ e*length_a.2_7
  length_a.3_7 ~~ e*length_a.3_7
  length_a.4_7 ~~ e*length_a.4_7
  length_a.5_7 ~~ e*length_a.5_7

  length_a.1_8 ~~ f*length_a.1_8
  length_a.2_8 ~~ f*length_a.2_8
  length_a.3_8 ~~ f*length_a.3_8
  length_a.4_8 ~~ f*length_a.4_8
  length_a.5_8 ~~ f*length_a.5_8

  length_a.1_9 ~~ g*length_a.1_9
  length_a.2_9 ~~ g*length_a.2_9
  length_a.3_9 ~~ g*length_a.3_9
  length_a.4_9 ~~ g*length_a.4_9
  length_a.5_9 ~~ g*length_a.5_9

  length_a.1_10 ~~ h*length_a.1_10
  length_a.2_10 ~~ h*length_a.2_10
  length_a.3_10 ~~ h*length_a.3_10
  length_a.4_10 ~~ h*length_a.4_10
  length_a.5_10 ~~ h*length_a.5_10

  length_a.1_11 ~~ i*length_a.1_11
  length_a.2_11 ~~ i*length_a.2_11
  length_a.3_11 ~~ i*length_a.3_11
  length_a.4_11 ~~ i*length_a.4_11
  length_a.5_11 ~~ i*length_a.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  length_a.1_2 ~ j*1
  length_a.2_2 ~ j*1
  length_a.3_2 ~ j*1
  length_a.4_2 ~ j*1
  length_a.5_2 ~ j*1

  length_a.1_3 ~ j*1
  length_a.2_3 ~ j*1
  length_a.3_3 ~ j*1
  length_a.4_3 ~ j*1
  length_a.5_3 ~ j*1

  length_a.1_4 ~ j*1
  length_a.2_4 ~ j*1
  length_a.3_4 ~ j*1
  length_a.4_4 ~ j*1
  length_a.5_4 ~ j*1

  length_a.1_5 ~ j*1
  length_a.2_5 ~ j*1
  length_a.3_5 ~ j*1
  length_a.4_5 ~ j*1
  length_a.5_5 ~ j*1

  length_a.1_6 ~ j*1
  length_a.2_6 ~ j*1
  length_a.3_6 ~ j*1
  length_a.4_6 ~ j*1
  length_a.5_6 ~ j*1

  length_a.1_7 ~ j*1
  length_a.2_7 ~ j*1
  length_a.3_7 ~ j*1
  length_a.4_7 ~ j*1
  length_a.5_7 ~ j*1

  length_a.1_8 ~ j*1
  length_a.2_8 ~ j*1
  length_a.3_8 ~ j*1
  length_a.4_8 ~ j*1
  length_a.5_8 ~ j*1

  length_a.1_9 ~ j*1
  length_a.2_9 ~ j*1
  length_a.3_9 ~ j*1
  length_a.4_9 ~ j*1
  length_a.5_9 ~ j*1

  length_a.1_10 ~ j*1
  length_a.2_10 ~ j*1
  length_a.3_10 ~ j*1
  length_a.4_10 ~ j*1
  length_a.5_10 ~ j*1

  length_a.1_11 ~ j*1
  length_a.2_11 ~ j*1
  length_a.3_11 ~ j*1
  length_a.4_11 ~ j*1
  length_a.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Flength_a_3 ~ 1
  Flength_a_4 ~ 1
  Flength_a_5 ~ 1
  Flength_a_6 ~ 1
  Flength_a_7 ~ 1
  Flength_a_8 ~ 1
  Flength_a_9 ~ 1
  Flength_a_10 ~ 1
  Flength_a_11 ~ 1


  '
  
  #Relationship length
  model_means_length_rl <- '

  #alters are identical thus equal loadings, variances and intercepts at each time point_

  #constrained loadings
  Frl_a_2 =~ 1*rl_a.1_2 + 1*rl_a.2_2 + 1*rl_a.3_2 +  1*rl_a.4_2 + 1*rl_a.5_2
  Frl_a_3 =~ 1*rl_a.1_3 + 1*rl_a.2_3 + 1*rl_a.3_3 +  1*rl_a.4_3 + 1*rl_a.5_3
  Frl_a_4 =~ 1*rl_a.1_4 + 1*rl_a.2_4 + 1*rl_a.3_4 +  1*rl_a.4_4 + 1*rl_a.5_4
  Frl_a_5 =~ 1*rl_a.1_5 + 1*rl_a.2_5 + 1*rl_a.3_5 +  1*rl_a.4_5 + 1*rl_a.5_5
  Frl_a_6 =~ 1*rl_a.1_6 + 1*rl_a.2_6 + 1*rl_a.3_6 +  1*rl_a.4_6 + 1*rl_a.5_6
  Frl_a_7 =~ 1*rl_a.1_7 + 1*rl_a.2_7 + 1*rl_a.3_7 +  1*rl_a.4_7 + 1*rl_a.5_7
  Frl_a_8 =~ 1*rl_a.1_8 + 1*rl_a.2_8 + 1*rl_a.3_8 +  1*rl_a.4_8 + 1*rl_a.5_8
  Frl_a_9 =~ 1*rl_a.1_9 + 1*rl_a.2_9 + 1*rl_a.3_9 +  1*rl_a.4_9 + 1*rl_a.5_9
  Frl_a_10 =~ 1*rl_a.1_10 + 1*rl_a.2_10 + 1*rl_a.3_10 +  1*rl_a.4_10 + 1*rl_a.5_10
  Frl_a_11 =~ 1*rl_a.1_11 + 1*rl_a.2_11 + 1*rl_a.3_11 +  1*rl_a.4_11 + 1*rl_a.5_11

  Frl_a_2 ~~ Frl_a_2
  Frl_a_3 ~~ Frl_a_3
  Frl_a_4 ~~ Frl_a_4
  Frl_a_5 ~~ Frl_a_5
  Frl_a_6 ~~ Frl_a_6
  Frl_a_7 ~~ Frl_a_7
  Frl_a_8 ~~ Frl_a_8
  Frl_a_9 ~~ Frl_a_9
  Frl_a_10 ~~ Frl_a_10
  Frl_a_11 ~~ Frl_a_11

  #constrained variances
  rl_a.1_2 ~~ x*rl_a.1_2
  rl_a.2_2 ~~ x*rl_a.2_2
  rl_a.3_2 ~~ x*rl_a.3_2
  rl_a.4_2 ~~ x*rl_a.4_2
  rl_a.5_2 ~~ x*rl_a.5_2

  rl_a.1_3 ~~ a*rl_a.1_3
  rl_a.2_3 ~~ a*rl_a.2_3
  rl_a.3_3 ~~ a*rl_a.3_3
  rl_a.4_3 ~~ a*rl_a.4_3
  rl_a.5_3 ~~ a*rl_a.5_3

  rl_a.1_4 ~~ b*rl_a.1_4
  rl_a.2_4 ~~ b*rl_a.2_4
  rl_a.3_4 ~~ b*rl_a.3_4
  rl_a.4_4 ~~ b*rl_a.4_4
  rl_a.5_4 ~~ b*rl_a.5_4

  rl_a.1_5 ~~ c*rl_a.1_5
  rl_a.2_5 ~~ c*rl_a.2_5
  rl_a.3_5 ~~ c*rl_a.3_5
  rl_a.4_5 ~~ c*rl_a.4_5
  rl_a.5_5 ~~ c*rl_a.5_5

  rl_a.1_6 ~~ d*rl_a.1_6
  rl_a.2_6 ~~ d*rl_a.2_6
  rl_a.3_6 ~~ d*rl_a.3_6
  rl_a.4_6 ~~ d*rl_a.4_6
  rl_a.5_6 ~~ d*rl_a.5_6

  rl_a.1_7 ~~ e*rl_a.1_7
  rl_a.2_7 ~~ e*rl_a.2_7
  rl_a.3_7 ~~ e*rl_a.3_7
  rl_a.4_7 ~~ e*rl_a.4_7
  rl_a.5_7 ~~ e*rl_a.5_7

  rl_a.1_8 ~~ f*rl_a.1_8
  rl_a.2_8 ~~ f*rl_a.2_8
  rl_a.3_8 ~~ f*rl_a.3_8
  rl_a.4_8 ~~ f*rl_a.4_8
  rl_a.5_8 ~~ f*rl_a.5_8

  rl_a.1_9 ~~ g*rl_a.1_9
  rl_a.2_9 ~~ g*rl_a.2_9
  rl_a.3_9 ~~ g*rl_a.3_9
  rl_a.4_9 ~~ g*rl_a.4_9
  rl_a.5_9 ~~ g*rl_a.5_9

  rl_a.1_10 ~~ h*rl_a.1_10
  rl_a.2_10 ~~ h*rl_a.2_10
  rl_a.3_10 ~~ h*rl_a.3_10
  rl_a.4_10 ~~ h*rl_a.4_10
  rl_a.5_10 ~~ h*rl_a.5_10

  rl_a.1_11 ~~ i*rl_a.1_11
  rl_a.2_11 ~~ i*rl_a.2_11
  rl_a.3_11 ~~ i*rl_a.3_11
  rl_a.4_11 ~~ i*rl_a.4_11
  rl_a.5_11 ~~ i*rl_a.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  rl_a.1_2 ~ j*1
  rl_a.2_2 ~ j*1
  rl_a.3_2 ~ j*1
  rl_a.4_2 ~ j*1
  rl_a.5_2 ~ j*1

  rl_a.1_3 ~ j*1
  rl_a.2_3 ~ j*1
  rl_a.3_3 ~ j*1
  rl_a.4_3 ~ j*1
  rl_a.5_3 ~ j*1

  rl_a.1_4 ~ j*1
  rl_a.2_4 ~ j*1
  rl_a.3_4 ~ j*1
  rl_a.4_4 ~ j*1
  rl_a.5_4 ~ j*1

  rl_a.1_5 ~ j*1
  rl_a.2_5 ~ j*1
  rl_a.3_5 ~ j*1
  rl_a.4_5 ~ j*1
  rl_a.5_5 ~ j*1

  rl_a.1_6 ~ j*1
  rl_a.2_6 ~ j*1
  rl_a.3_6 ~ j*1
  rl_a.4_6 ~ j*1
  rl_a.5_6 ~ j*1

  rl_a.1_7 ~ j*1
  rl_a.2_7 ~ j*1
  rl_a.3_7 ~ j*1
  rl_a.4_7 ~ j*1
  rl_a.5_7 ~ j*1

  rl_a.1_8 ~ j*1
  rl_a.2_8 ~ j*1
  rl_a.3_8 ~ j*1
  rl_a.4_8 ~ j*1
  rl_a.5_8 ~ j*1

  rl_a.1_9 ~ j*1
  rl_a.2_9 ~ j*1
  rl_a.3_9 ~ j*1
  rl_a.4_9 ~ j*1
  rl_a.5_9 ~ j*1

  rl_a.1_10 ~ j*1
  rl_a.2_10 ~ j*1
  rl_a.3_10 ~ j*1
  rl_a.4_10 ~ j*1
  rl_a.5_10 ~ j*1

  rl_a.1_11 ~ j*1
  rl_a.2_11 ~ j*1
  rl_a.3_11 ~ j*1
  rl_a.4_11 ~ j*1
  rl_a.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Frl_a_3 ~ 1
  Frl_a_4 ~ 1
  Frl_a_5 ~ 1
  Frl_a_6 ~ 1
  Frl_a_7 ~ 1
  Frl_a_8 ~ 1
  Frl_a_9 ~ 1
  Frl_a_10 ~ 1
  Frl_a_11 ~ 1


  '
  
  #average similarity
  model_means_sim <- '

  #alters are identical thus equal loadings, variances and intercepts at each time point_

  #constrained loadings
  Fave_sim_1 =~ 1*ave_sim.1_1 + 1*ave_sim.2_1 + 1*ave_sim.3_1 +  1*ave_sim.4_1 + 1*ave_sim.5_1
  Fave_sim_2 =~ 1*ave_sim.1_2 + 1*ave_sim.2_2 + 1*ave_sim.3_2 +  1*ave_sim.4_2 + 1*ave_sim.5_2
  Fave_sim_3 =~ 1*ave_sim.1_3 + 1*ave_sim.2_3 + 1*ave_sim.3_3 +  1*ave_sim.4_3 + 1*ave_sim.5_3
  Fave_sim_4 =~ 1*ave_sim.1_4 + 1*ave_sim.2_4 + 1*ave_sim.3_4 +  1*ave_sim.4_4 + 1*ave_sim.5_4
  Fave_sim_5 =~ 1*ave_sim.1_5 + 1*ave_sim.2_5 + 1*ave_sim.3_5 +  1*ave_sim.4_5 + 1*ave_sim.5_5
  Fave_sim_6 =~ 1*ave_sim.1_6 + 1*ave_sim.2_6 + 1*ave_sim.3_6 +  1*ave_sim.4_6 + 1*ave_sim.5_6
  Fave_sim_7 =~ 1*ave_sim.1_7 + 1*ave_sim.2_7 + 1*ave_sim.3_7 +  1*ave_sim.4_7 + 1*ave_sim.5_7
  Fave_sim_8 =~ 1*ave_sim.1_8 + 1*ave_sim.2_8 + 1*ave_sim.3_8 +  1*ave_sim.4_8 + 1*ave_sim.5_8
  Fave_sim_9 =~ 1*ave_sim.1_9 + 1*ave_sim.2_9 + 1*ave_sim.3_9 +  1*ave_sim.4_9 + 1*ave_sim.5_9
  Fave_sim_10 =~ 1*ave_sim.1_10 + 1*ave_sim.2_10 + 1*ave_sim.3_10 +  1*ave_sim.4_10 + 1*ave_sim.5_10
  Fave_sim_11 =~ 1*ave_sim.1_11 + 1*ave_sim.2_11 + 1*ave_sim.3_11 +  1*ave_sim.4_11 + 1*ave_sim.5_11


  Fave_sim_1 ~~ Fave_sim_1
  Fave_sim_2 ~~ Fave_sim_2
  Fave_sim_3 ~~ Fave_sim_3
  Fave_sim_4 ~~ Fave_sim_4
  Fave_sim_5 ~~ Fave_sim_5
  Fave_sim_6 ~~ Fave_sim_6
  Fave_sim_7 ~~ Fave_sim_7
  Fave_sim_8 ~~ Fave_sim_8
  Fave_sim_9 ~~ Fave_sim_9
  Fave_sim_10 ~~ Fave_sim_10
  Fave_sim_11 ~~ Fave_sim_11

  #constrained variances
  ave_sim.1_1 ~~ x*ave_sim.1_1
  ave_sim.2_1 ~~ x*ave_sim.2_1
  ave_sim.3_1 ~~ x*ave_sim.3_1
  ave_sim.4_1 ~~ x*ave_sim.4_1
  ave_sim.5_1 ~~ x*ave_sim.5_1

  ave_sim.1_2 ~~ z*ave_sim.1_2
  ave_sim.2_2 ~~ z*ave_sim.2_2
  ave_sim.3_2 ~~ z*ave_sim.3_2
  ave_sim.4_2 ~~ z*ave_sim.4_2
  ave_sim.5_2 ~~ z*ave_sim.5_2

  ave_sim.1_3 ~~ a*ave_sim.1_3
  ave_sim.2_3 ~~ a*ave_sim.2_3
  ave_sim.3_3 ~~ a*ave_sim.3_3
  ave_sim.4_3 ~~ a*ave_sim.4_3
  ave_sim.5_3 ~~ a*ave_sim.5_3

  ave_sim.1_4 ~~ b*ave_sim.1_4
  ave_sim.2_4 ~~ b*ave_sim.2_4
  ave_sim.3_4 ~~ b*ave_sim.3_4
  ave_sim.4_4 ~~ b*ave_sim.4_4
  ave_sim.5_4 ~~ b*ave_sim.5_4

  ave_sim.1_5 ~~ c*ave_sim.1_5
  ave_sim.2_5 ~~ c*ave_sim.2_5
  ave_sim.3_5 ~~ c*ave_sim.3_5
  ave_sim.4_5 ~~ c*ave_sim.4_5
  ave_sim.5_5 ~~ c*ave_sim.5_5

  ave_sim.1_6 ~~ d*ave_sim.1_6
  ave_sim.2_6 ~~ d*ave_sim.2_6
  ave_sim.3_6 ~~ d*ave_sim.3_6
  ave_sim.4_6 ~~ d*ave_sim.4_6
  ave_sim.5_6 ~~ d*ave_sim.5_6

  ave_sim.1_7 ~~ e*ave_sim.1_7
  ave_sim.2_7 ~~ e*ave_sim.2_7
  ave_sim.3_7 ~~ e*ave_sim.3_7
  ave_sim.4_7 ~~ e*ave_sim.4_7
  ave_sim.5_7 ~~ e*ave_sim.5_7

  ave_sim.1_8 ~~ f*ave_sim.1_8
  ave_sim.2_8 ~~ f*ave_sim.2_8
  ave_sim.3_8 ~~ f*ave_sim.3_8
  ave_sim.4_8 ~~ f*ave_sim.4_8
  ave_sim.5_8 ~~ f*ave_sim.5_8

  ave_sim.1_9 ~~ g*ave_sim.1_9
  ave_sim.2_9 ~~ g*ave_sim.2_9
  ave_sim.3_9 ~~ g*ave_sim.3_9
  ave_sim.4_9 ~~ g*ave_sim.4_9
  ave_sim.5_9 ~~ g*ave_sim.5_9

  ave_sim.1_10 ~~ h*ave_sim.1_10
  ave_sim.2_10 ~~ h*ave_sim.2_10
  ave_sim.3_10 ~~ h*ave_sim.3_10
  ave_sim.4_10 ~~ h*ave_sim.4_10
  ave_sim.5_10 ~~ h*ave_sim.5_10

  ave_sim.1_11 ~~ i*ave_sim.1_11
  ave_sim.2_11 ~~ i*ave_sim.2_11
  ave_sim.3_11 ~~ i*ave_sim.3_11
  ave_sim.4_11 ~~ i*ave_sim.4_11
  ave_sim.5_11 ~~ i*ave_sim.5_11

  #constrained intercepts / we want structural changes to be picked up by the factor
  ave_sim.1_1 ~ j*1
  ave_sim.2_1 ~ j*1
  ave_sim.3_1 ~ j*1
  ave_sim.4_1 ~ j*1
  ave_sim.5_1 ~ j*1

  ave_sim.1_2 ~ j*1
  ave_sim.2_2 ~ j*1
  ave_sim.3_2 ~ j*1
  ave_sim.4_2 ~ j*1
  ave_sim.5_2 ~ j*1

  ave_sim.1_3 ~ j*1
  ave_sim.2_3 ~ j*1
  ave_sim.3_3 ~ j*1
  ave_sim.4_3 ~ j*1
  ave_sim.5_3 ~ j*1

  ave_sim.1_4 ~ j*1
  ave_sim.2_4 ~ j*1
  ave_sim.3_4 ~ j*1
  ave_sim.4_4 ~ j*1
  ave_sim.5_4 ~ j*1

  ave_sim.1_5 ~ j*1
  ave_sim.2_5 ~ j*1
  ave_sim.3_5 ~ j*1
  ave_sim.4_5 ~ j*1
  ave_sim.5_5 ~ j*1

  ave_sim.1_6 ~ j*1
  ave_sim.2_6 ~ j*1
  ave_sim.3_6 ~ j*1
  ave_sim.4_6 ~ j*1
  ave_sim.5_6 ~ j*1

  ave_sim.1_7 ~ j*1
  ave_sim.2_7 ~ j*1
  ave_sim.3_7 ~ j*1
  ave_sim.4_7 ~ j*1
  ave_sim.5_7 ~ j*1

  ave_sim.1_8 ~ j*1
  ave_sim.2_8 ~ j*1
  ave_sim.3_8 ~ j*1
  ave_sim.4_8 ~ j*1
  ave_sim.5_8 ~ j*1

  ave_sim.1_9 ~ j*1
  ave_sim.2_9 ~ j*1
  ave_sim.3_9 ~ j*1
  ave_sim.4_9 ~ j*1
  ave_sim.5_9 ~ j*1

  ave_sim.1_10 ~ j*1
  ave_sim.2_10 ~ j*1
  ave_sim.3_10 ~ j*1
  ave_sim.4_10 ~ j*1
  ave_sim.5_10 ~ j*1

  ave_sim.1_11 ~ j*1
  ave_sim.2_11 ~ j*1
  ave_sim.3_11 ~ j*1
  ave_sim.4_11 ~ j*1
  ave_sim.5_11 ~ j*1

  # Free latent means from t = 2 onward.
  Fave_sim_2 ~ 1
  Fave_sim_3 ~ 1
  Fave_sim_4 ~ 1
  Fave_sim_5 ~ 1
  Fave_sim_6 ~ 1
  Fave_sim_7 ~ 1
  Fave_sim_8 ~ 1
  Fave_sim_9 ~ 1
  Fave_sim_10 ~ 1
  Fave_sim_11 ~ 1

'
  
  #combine lavaan models
  lavaan_models <- list(model_means_educ_a,
                        model_means_pol,
                        model_means_educ_orig_a,
                        model_means_length,
                        model_means_length_rl,
                        model_means_sim)
  
  
  # paralellize the estimation
  numCores <- detectCores()
  registerDoParallel(core = 6)
  
  #initialize foreach loop
  model_list <- foreach(a = 1:6, #a = 1
          .packages = c("tidyverse",
                        "lavaan")) %dopar% {
                          lavaan(
                            lavaan_models[[a]],
                            data = x,
                            missing = 'ML',
                            fixed.x = FALSE,
                            meanstructure = T
                          )
                        }
  
   df_list <- foreach(a = 1:6,
                      .packages = "tidyverse") %dopar% {
     data.frame(x, predict(model_list[[a]])) %>%
                            select(nomem_encr,starts_with("F")) %>% 
                          select(-starts_with("female"))
     }
                        
  #stop parralellization
  stopImplicitCluster()
  
  #combine results and predicted means
  df_results <- x %>%
    left_join(df_list[[1]], by = "nomem_encr") %>%
    left_join(df_list[[2]], by = "nomem_encr") %>%
    left_join(df_list[[3]], by = "nomem_encr") %>%
    left_join(df_list[[4]], by = "nomem_encr") %>% 
    left_join(df_list[[5]], by = "nomem_encr") %>% 
    left_join(df_list[[6]], by = "nomem_encr")
  
  #name list
  names(model_list) <- c("means_educ_fit",
                         "means_pol_fit",
                         "means_educ_orig_fit",
                         "means_length_fit",
                         "means_rl_fit",
                         "means_sim_fit")
  
  #create list with results and predicted means
  predicted_means_result <- list(df_results,
                                 model_list)
  
  #edit names in list
  names(predicted_means_result) <- c("df_combined",
                                     "models")
  return(predicted_means_result)
}

Robustness Data creation

No sibling data

no_sibling_ids <- mlsem_datafiles[[2]] %>% 
  select(nomem_encr, starts_with("rel_a")) %>% 
  pivot_longer(cols = 2:56,
               names_to = c("measure", "alter", "wave"),
               values_to = "value",
               names_sep = "_") %>% 
  group_by(nomem_encr,alter) %>% 
  mutate(selection = as.numeric(value == 3)) %>% 
  group_by(nomem_encr) %>% 
  mutate(select_id = max(selection, na.rm = T)) %>% 
  select(nomem_encr, select_id) %>% 
  distinct() %>% 
  filter(select_id == 0) %>% 
  pull(nomem_encr)


no_sibling_data_strict <- mlsem_datafiles[[2]] %>% 
  filter(nomem_encr %in% no_sibling_ids)

# text <- mlsem_data %>% 
#   select(nomem_encr, matches("_a.")) %>% 
#   pivot_longer(cols = 2:ncol(.),
#                names_to = c("measure", "alter", "wave"),
#                values_to = "value",
#                names_sep = "_") %>% 
#   mutate(variable = paste0(measure, "_", alter),
#          alter = as.numeric(str_extract(.$alter, pattern = "[[:digit:]]")),
#          wave = as.numeric(wave)) %>% 
#   select(nomem_encr, alter, variable, wave, value) %>% 
#   pivot_wider(id_cols = c(nomem_encr, alter, wave),
#               names_from = "variable", 
#               values_from = "value",
#               values_fill = NA)

Estimate means

#create file names
file_name_predresults <- "results/predicted_means/240816_pred-means-cleaned-df.Rdata"
file_name_compl <- "results/predicted_means/240816_pred-means-compl-cleaned-df.Rdata"
file_name_no_sibling <- "results/predicted_means/240816_pred-means-nosibling-cleaned-df.Rdata"
file_name_no_sibling1 <- "results/predicted_means/240816_pred-means-nosibling1-cleaned-df.Rdata"

#main results
if(!file.exists(file_name_predresults)){
  pred_results <- f_bias_corrected_means(mlsem_datafiles[[2]])
  save(pred_results, 
       file = file_name_predresults)
} else(
  load(file = file_name_predresults)
)

[1] “pred_results”

#without siblings
if(!file.exists(file_name_no_sibling1)){
  pred_results_no_sibling1 <- f_bias_corrected_means(mlsem_datafiles_robustness[[2]])
  save(pred_results_no_sibling1, 
       file = file_name_no_sibling1)
} else(
  load(file = file_name_no_sibling1)
)

[1] “pred_results_no_sibling1”

#without siblings2
if(!file.exists(file_name_no_sibling)){
  pred_results_no_sibling2 <- f_bias_corrected_means(no_sibling_data_strict)
  save(pred_results_no_sibling2, 
       file = file_name_no_sibling)
} else(
  load(file = file_name_no_sibling)
)

[1] “pred_results_no_sibling”

#complete sample
if(!file.exists(file_name_no_sibling)){
  pred_results_compl <- f_bias_corrected_means(mlsem_datafiles[[1]])
  save(pred_results_compl, 
       file = file_name_compl)
} else(
  load(file = file_name_compl)
)

[1] “pred_results_compl”

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