From 98361701ebecbeaa87f00145ba222b06104d6906 Mon Sep 17 00:00:00 2001
From: wwang93 <142034236+wwang93@users.noreply.github.com>
Date: Sun, 19 Nov 2023 19:47:02 -0500
Subject: [PATCH] Update cop_pse_auxiliary.R

Fix those lines of code in cop_pse_auxiliary.R that are longer than 80 characters.
Except for this part:
cal_pse <- function(thr, kryx)
  # calculations for preserving standard error
----
(the formula for calculations stays the same)
---
 R/cop_pse_auxiliary.R | 134 +++++++++++++++++++++++++++---------------
 1 file changed, 87 insertions(+), 47 deletions(-)

diff --git a/R/cop_pse_auxiliary.R b/R/cop_pse_auxiliary.R
index cc958b81..1adca840 100644
--- a/R/cop_pse_auxiliary.R
+++ b/R/cop_pse_auxiliary.R
@@ -21,7 +21,16 @@ cal_rxy <- function(ryxGz, rxz, ryz){
     return(rxy)
 }
 
-cal_delta_star <- function(FR2max, R2, R2_uncond, est_eff, eff_thr, var_x, var_y, est_uncond, rxz, n_obs){
+cal_delta_star <- function(FR2max,
+                           R2, 
+                           R2_uncond, 
+                           est_eff, 
+                           eff_thr, 
+                           var_x, 
+                           var_y, 
+                           est_uncond, 
+                           rxz, 
+                           n_obs){
     if (FR2max > .99) {FR2max = .99}
     # if (FR2max < R2 + inci) {FR2max = R2 + inci} check with Ken what this means
     if (FR2max > R2) {D = sqrt(FR2max - R2)}
@@ -35,7 +44,9 @@ cal_delta_star <- function(FR2max, R2, R2_uncond, est_eff, eff_thr, var_x, var_y
     t_x = var_x * (n_obs / (n_obs - 1)) * (1 - rxz^2)
     ## adjust df for var_x 
     ## var_x is population variance, need sample variance from x
-    ## this adjustment is to get closer to what robomit generates as they run regression using the sample data 
+    ## this adjustment is to get closer to what robomit generates 
+    ##   as they run regression using the sample data 
+    
     num1 = bt_m_b * rt_m_ro_t_syy * t_x
     num2 = bt_m_b * var_x * t_x * b0_m_b1^2
     num3 = 2 * bt_m_b^2 * (t_x * b0_m_b1 * var_x)
@@ -128,19 +139,29 @@ verify_reg_Gzcv = function(n_obs, sdx, sdy, sdz, sdcv,
         }
     )
     #if model can be run to verify true delta, then run it can save results
-    if (class(flag_cov) == "lavaan") {
-        fit <- lavaan::sem(model,
-                      sample.cov = cov.matrix,
-                      sample.nobs = n_obs)
-        ## the R2 extracted from summary is NOT right, do the calculation below
-        R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[4,]$est) / sdy^2
-        betaX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$est
-        seX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$se
-        betaZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$est
-        seZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$se
-        betaCV <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta3',]$est
-        seCV <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta3',]$se
-    }
+ if (class(flag_cov) == "lavaan") {
+  fit <- lavaan::sem(
+    model,
+    sample.cov = cov.matrix,
+    sample.nobs = n_obs
+  )
+  ## the R2 extracted from summary is NOT right, do the calculation below
+  R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[4, ]$est) / sdy^2
+  betaX <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta1", ]$est
+  seX <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta1", ]$se
+  betaZ <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta2", ]$est
+  seZ <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta2", ]$se
+  betaCV <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta3", ]$est
+  seCV <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == "beta3", ]$se
+}
+
+
 
     #get regression based on true delta in terms of standardized coefficent
     cor.matrix <- matrix(c(1,rxy, rzy, rcvy,
@@ -167,18 +188,25 @@ verify_reg_Gzcv = function(n_obs, sdx, sdy, sdz, sdcv,
     )
     
     # if model can be run, then run it
-    if (class(flag_cor) == "lavaan") {
-        fit <- lavaan::sem(model,
-                   sample.cov = cor.matrix,
-                   sample.nobs = n_obs)
-        std_R2 <- 1 - lavaan::parameterEstimates(fit)[4,]$est
-        std_betaX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$est
-        std_seX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$se
-        std_betaZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$est
-        std_seZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$se
-        std_betaCV <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta3',]$est
-        std_seCV <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta3',]$se
-    }
+ if (class(flag_cor) == "lavaan") {
+    fit <- lavaan::sem(model,
+      sample.cov = cor.matrix,
+      sample.nobs = n_obs)
+    std_R2 <- 1 - lavaan::parameterEstimates(fit)[4, ]$est
+    std_betaX <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta1', ]$est
+    std_seX <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta1', ]$se
+    std_betaZ <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta2', ]$est
+    std_seZ <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta2', ]$se
+    std_betaCV <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta3', ]$est
+    std_seCV <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == 'beta3', ]$se
+}
+
     
     if (class(flag_cor) == "lavaan" && class(flag_cov) == "lavaan") {
         result = list(R2, betaX, seX, betaZ, seZ, betaCV, seCV,
@@ -223,7 +251,8 @@ cal_pse <- function(thr, kryx){
 }
 
 verify_manual <- function(rxy, rxz, rxcv, ryz, rycv, rzcv, sdy, sdx){
-    beta <- (rxy + rycv * rxz * rzcv + ryz * rxcv * rzcv - rxy * rzcv^2 - rycv * rxcv - ryz * rxz) /
+    beta <- (rxy + rycv * rxz * rzcv + ryz * rxcv * rzcv - 
+             rxy * rzcv^2 - rycv * rxcv - ryz * rxz) /
         (1 + 2 * rxcv * rzcv * rxz - rxcv^2 - rzcv^2 - rxz^2)
     eff <- beta * sdy / sdx
     return(beta)
@@ -261,16 +290,22 @@ verify_reg_Gz = function(n_obs, sdx, sdy, sdz, rxy, rxz, rzy){
     )
     #if model can be run to verify true delta, then run it can save results
     if (class(flag_cov) == "lavaan") {
-        fit <- lavaan::sem(model,
-                   sample.cov = cov.matrix,
-                   sample.nobs = n_obs)
-        ## the R2 extracted from summary is NOT right, do the calculation below
-        R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[3,]$est) / sdy^2
-        betaX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$est
-        seX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$se
-        betaZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$est
-        seZ <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta2',]$se
-   }
+    fit <- lavaan::sem(model,
+      sample.cov = cov.matrix,
+      sample.nobs = n_obs
+    )
+    ## the R2 extracted from summary is NOT right, do the calculation below
+    R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[3, ]$est) / sdy^2
+    betaX <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == "beta1", ]$est
+    seX <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == "beta1", ]$se
+    betaZ <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == "beta2", ]$est
+    seZ <- lavaan::parameterEstimates(fit)[
+      lavaan::parameterEstimates(fit)$label == "beta2", ]$se
+}
+
 
     if (class(flag_cov) == "lavaan") {
         result = list(R2, betaX, seX, betaZ, seZ)
@@ -307,15 +342,20 @@ verify_reg_uncond = function(n_obs, sdx, sdy, rxy){
         }
     )
     #if model can be run to verify true delta, then run it can save results
-    if (class(flag_cov) == "lavaan") {
-        fit <- lavaan::sem(model,
-                   sample.cov = cov.matrix,
-                   sample.nobs = n_obs)
-        ## the R2 extracted from summary is NOT right, do the calculation below
-        R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[2,]$est) / sdy^2
-        betaX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$est
-        seX <- lavaan::parameterEstimates(fit)[lavaan::parameterEstimates(fit)$label == 'beta1',]$se
-    }
+  if (class(flag_cov) == "lavaan") {
+  fit <- lavaan::sem(
+    model,
+    sample.cov = cov.matrix,
+    sample.nobs = n_obs
+  )
+  ## the R2 extracted from summary is NOT right, do the calculation below
+  R2 <- (sdy^2 - lavaan::parameterEstimates(fit)[2, ]$est) / sdy^2
+  betaX <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == 'beta1', ]$est
+  seX <- lavaan::parameterEstimates(fit)[
+    lavaan::parameterEstimates(fit)$label == 'beta1', ]$se
+}
+
     
     if (class(flag_cov) == "lavaan") {
         result = list(R2, betaX, seX)