Last updated: 2020-06-10

Checks: 6 1

Knit directory: mcfa-para-est/

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Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/compiled_para_results.txt
    Ignored:    data/results_bias_est.csv
    Ignored:    data/results_bias_se.csv
    Ignored:    fig/
    Ignored:    manuscript/
    Ignored:    output/fact-cov-converge-largeN.pdf
    Ignored:    output/fact-cov-converge-medN.pdf
    Ignored:    output/fact-cov-converge-smallN.pdf
    Ignored:    output/loading-converge-largeN.pdf
    Ignored:    output/loading-converge-medN.pdf
    Ignored:    output/loading-converge-smallN.pdf
    Ignored:    references/
    Ignored:    sera-presentation/

Untracked files:
    Untracked:  analysis/ml-cfa-parameter-anova-estimates.Rmd
    Untracked:  analysis/ml-cfa-parameter-anova-relative-bias.Rmd
    Untracked:  analysis/ml-cfa-parameter-bias-latent-ICC.Rmd
    Untracked:  analysis/ml-cfa-parameter-bias-observed-ICC.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-L1-factor-covariance.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-L2-factor-covariance.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-L2-factor-variance.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-L2-residual-variance.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-factor-loadings.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-latent-ICC.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-ARD-observed-ICC.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-correlation-pubfigure.Rmd
    Untracked:  analysis/ml-cfa-parameter-convergence-trace-plots-factor-loadings.Rmd
    Untracked:  analysis/ml-cfa-standard-error-anova-logSE.Rmd
    Untracked:  analysis/ml-cfa-standard-error-anova-relative-bias.Rmd
    Untracked:  analysis/ml-cfa-standard-error-bias-factor-loadings.Rmd
    Untracked:  analysis/ml-cfa-standard-error-bias-level1-factor-covariances.Rmd
    Untracked:  analysis/ml-cfa-standard-error-bias-level2-factor-covariances.Rmd
    Untracked:  analysis/ml-cfa-standard-error-bias-level2-factor-variances.Rmd
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    Untracked:  analysis/ml-cfa-standard-error-bias-overview.Rmd
    Untracked:  code/r_functions.R
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    Untracked:  renv/

Unstaged changes:
    Modified:   .gitignore
    Modified:   analysis/index.Rmd
    Modified:   analysis/ml-cfa-convergence-summary.Rmd
    Modified:   analysis/ml-cfa-parameter-convergence-correlation-factor-loadings.Rmd
    Modified:   code/get_data.R
    Modified:   code/load_packages.R

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The purpose of this page is the identify the degree of separation between estimates of parameters between estimation methods.

Packages and Set-Up

rm(list=ls())
source(paste0(getwd(),"/code/load_packages.R"))
source(paste0(getwd(),"/code/get_data.R"))
source(paste0(getwd(),"/code/r_functions.R"))

# general options
theme_set(theme_bw())
options(digits=3)

##Chunk iptions
knitr::opts_chunk$set(out.width="225%")

Data Management

# set up vectors of variable names
pvec <- c(paste0('lambda1',1:6), paste0('lambda2',6:10), 'psiW12','psiB1', 'psiB2', 'psiB12', paste0('thetaB',1:10), 'icc_lv1_est', 'icc_lv2_est', paste0('icc_ov',1:10,'_est'))
# stored "true" values of parameters by each condition
ptvec <- c(rep('lambdaT',11), 'psiW12T', 'psiB1T', 'psiB2T', 'psiB12T', rep("thetaBT", 10), rep('icc_lv',2), rep('icc_ov',10))


# take out non-converged/inadmissible cases
sim_results <- filter(sim_results, Converge==1, Admissible==1)

# Set conditions levels as categorical values
sim_results <- sim_results %>%
  mutate(N1 = factor(N1, c("5", "10", "30")),
         N2 = factor(N2, c("30", "50", "100", "200")),
         ICC_OV = factor(ICC_OV, c("0.1","0.3", "0.5")),
         ICC_LV = factor(ICC_LV, c("0.1", "0.5")))

# convert to long format
long_res1 <- sim_results[,c("Condition", "Replication", "N1", "N2", "ICC_OV", "ICC_LV", "Estimator", pvec)] %>%
  pivot_longer(
    cols = all_of(pvec),
    names_to = "Parameter",
    values_to = "Estimate"
  )

long_res2 <- tibble(sim_results[,c("Condition", "Replication", "N1", "N2", "ICC_OV", "ICC_LV", "Estimator", ptvec)], .name_repair="universal")
ptvec <- colnames(long_res2)[8:44]
long_res2 <- long_res2 %>%
  pivot_longer(
    cols = all_of(ptvec),
    names_to = "ParameterT",
    values_to = "Truth"
  )

long_results <- long_res1
long_results$ParameterT <- long_res2$ParameterT
long_results$Truth <- long_res2$Truth

# Now, make "wider"
wide_res <- long_results %>%
  pivot_wider(
    names_from = "Estimator",
    values_from = "Estimate"
  )


# Subset to just latent variable ICC
wide_res <- filter(wide_res, Parameter %like% "icc_lv")

Estimate Relative Difference

wide_res <- wide_res %>%
  mutate(
    MLR_ULSMV = ((MLR - ULSMV))/Truth*100,
    MLR_WLSMV = ((MLR - WLSMV))/Truth*100,
    ULSMV_WLSMV = ((ULSMV - WLSMV))/Truth*100
  )
long_results <- wide_res %>%
  pivot_longer(
    cols= all_of(c("MLR_ULSMV", "MLR_WLSMV", "ULSMV_WLSMV")),
    names_to = "Comparison",
    values_to = "ARD"
  )

ard.est <- long_results %>%
  group_by(Condition, N1, N2, ICC_OV, ICC_LV, Comparison) %>%
  summarise(
    ARD = mean(ARD, na.rm=T)
  )


ard.est$Comparison <- factor(ard.est$Comparison,
                      levels=c("MLR_ULSMV", "MLR_WLSMV", "ULSMV_WLSMV"),
                      labels=c("MLR/ULSMV)",
                               "MLR/WLSMV)",
                               "ULSMV/WLSMV)"),
                      ordered=T)

Single Conditions

All Conditions

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL,
       title="ARD: Latent ICC")+
  theme_bw()+
  theme(panel.grid = element_blank())
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

By Level-1 Sample Size

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL,
       title="ARD: Latent ICC",
       subtitle = "Conditional on Level-1 Sample Size")+
  #scale_color_manual(name="% Admissible", values=cols)+
  facet_wrap(.~N1)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        axis.text.x = element_text(angle=90))
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

By Level-2 Sample Size

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL,
       title="ARD: Latent ICC",
       subtitle = "Conditional on Level-2 Sample Size")+
  #scale_color_manual(name="% Admissible", values=cols)+
  facet_wrap(.~N2, nrow=1)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        axis.text.x = element_text(angle=90))
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

By Observed Variable ICC

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL,
       title="ARD: Latent ICC",
       subtitle = "Conditional on Observed Variable ICC")+
  #scale_color_manual(name="% Admissible", values=cols)+
  facet_wrap(.~ICC_OV)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        axis.text.x = element_text(angle=90))
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

By Latent Variable ICC

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL,
       title="ARD: Latent ICC",
       subtitle = "Conditional on Latent Variable ICC")+
  #scale_color_manual(name="% Admissible", values=cols)+
  facet_wrap(.~ICC_LV)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        axis.text.x = element_text(angle=90))
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

Publication Figure

p <- ggplot(ard.est, aes(x=Comparison, y=ARD)) +
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(width=0.3, size=2, alpha=0.7) +
  geom_hline(yintercept = 10, color="red")+
  geom_hline(yintercept = -10, color="red")+
  scale_y_continuous(limits=c(-100, 100), breaks=c(-100, -60, -30, -10, 0, 10, 30, 60, 100))+
  labs(y="Average Relative Difference",
       x=NULL)+
  theme_bw()+
  theme(panel.grid = element_blank(),
        legend.position = c(0.5,0.25),
        legend.text = element_text(size=12),
        legend.title = element_text(size=12),
        axis.title.y = element_text(size=12),
        axis.text.y = element_text(size=10),
        axis.text.x = element_text(angle=20, hjust=1,
                                   vjust = 1, size=12))
p
Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (geom_point).

#ggsave("fig/estimate_correlation_factor_loading.pdf",p, units="in", height=3.5, width=5)
sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] xtable_1.8-4          kableExtra_1.1.0      cowplot_1.0.0        
 [4] MplusAutomation_0.7-3 data.table_1.12.8     patchwork_1.0.0      
 [7] forcats_0.5.0         stringr_1.4.0         dplyr_0.8.5          
[10] purrr_0.3.4           readr_1.3.1           tidyr_1.1.0          
[13] tibble_3.0.1          ggplot2_3.3.0         tidyverse_1.3.0      
[16] workflowr_1.6.2      

loaded via a namespace (and not attached):
 [1] httr_1.4.1        jsonlite_1.6.1    viridisLite_0.3.0 gsubfn_0.7       
 [5] modelr_0.1.8      assertthat_0.2.1  pander_0.6.3      blob_1.2.1       
 [9] cellranger_1.1.0  yaml_2.2.1        pillar_1.4.4      backports_1.1.7  
[13] lattice_0.20-38   glue_1.4.1        digest_0.6.25     promises_1.1.0   
[17] rvest_0.3.5       colorspace_1.4-1  htmltools_0.4.0   httpuv_1.5.2     
[21] plyr_1.8.6        pkgconfig_2.0.3   broom_0.5.6       haven_2.3.0      
[25] scales_1.1.1      webshot_0.5.2     later_1.0.0       git2r_0.27.1     
[29] generics_0.0.2    farver_2.0.3      ellipsis_0.3.1    withr_2.2.0      
[33] cli_2.0.2         proto_1.0.0       magrittr_1.5      crayon_1.3.4     
[37] readxl_1.3.1      evaluate_0.14     fs_1.4.1          fansi_0.4.1      
[41] nlme_3.1-144      xml2_1.3.2        tools_3.6.3       hms_0.5.3        
[45] lifecycle_0.2.0   munsell_0.5.0     reprex_0.3.0      compiler_3.6.3   
[49] rlang_0.4.6       grid_3.6.3        rstudioapi_0.11   texreg_1.36.23   
[53] rmarkdown_2.1     boot_1.3-24       gtable_0.3.0      DBI_1.1.0        
[57] R6_2.4.1          lubridate_1.7.8   knitr_1.28        rprojroot_1.3-2  
[61] stringi_1.4.6     parallel_3.6.3    Rcpp_1.0.4.6      vctrs_0.3.0      
[65] dbplyr_1.4.4      tidyselect_1.1.0  xfun_0.14         coda_0.19-3      

sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] xtable_1.8-4          kableExtra_1.1.0      cowplot_1.0.0        
 [4] MplusAutomation_0.7-3 data.table_1.12.8     patchwork_1.0.0      
 [7] forcats_0.5.0         stringr_1.4.0         dplyr_0.8.5          
[10] purrr_0.3.4           readr_1.3.1           tidyr_1.1.0          
[13] tibble_3.0.1          ggplot2_3.3.0         tidyverse_1.3.0      
[16] workflowr_1.6.2      

loaded via a namespace (and not attached):
 [1] httr_1.4.1        jsonlite_1.6.1    viridisLite_0.3.0 gsubfn_0.7       
 [5] modelr_0.1.8      assertthat_0.2.1  pander_0.6.3      blob_1.2.1       
 [9] cellranger_1.1.0  yaml_2.2.1        pillar_1.4.4      backports_1.1.7  
[13] lattice_0.20-38   glue_1.4.1        digest_0.6.25     promises_1.1.0   
[17] rvest_0.3.5       colorspace_1.4-1  htmltools_0.4.0   httpuv_1.5.2     
[21] plyr_1.8.6        pkgconfig_2.0.3   broom_0.5.6       haven_2.3.0      
[25] scales_1.1.1      webshot_0.5.2     later_1.0.0       git2r_0.27.1     
[29] generics_0.0.2    farver_2.0.3      ellipsis_0.3.1    withr_2.2.0      
[33] cli_2.0.2         proto_1.0.0       magrittr_1.5      crayon_1.3.4     
[37] readxl_1.3.1      evaluate_0.14     fs_1.4.1          fansi_0.4.1      
[41] nlme_3.1-144      xml2_1.3.2        tools_3.6.3       hms_0.5.3        
[45] lifecycle_0.2.0   munsell_0.5.0     reprex_0.3.0      compiler_3.6.3   
[49] rlang_0.4.6       grid_3.6.3        rstudioapi_0.11   texreg_1.36.23   
[53] rmarkdown_2.1     boot_1.3-24       gtable_0.3.0      DBI_1.1.0        
[57] R6_2.4.1          lubridate_1.7.8   knitr_1.28        rprojroot_1.3-2  
[61] stringi_1.4.6     parallel_3.6.3    Rcpp_1.0.4.6      vctrs_0.3.0      
[65] dbplyr_1.4.4      tidyselect_1.1.0  xfun_0.14         coda_0.19-3