diff --git a/R/back_transformations.R b/R/back_transformations.R
index 9b2254f..a7b90f4 100644
--- a/R/back_transformations.R
+++ b/R/back_transformations.R
@@ -25,12 +25,10 @@ log_back <- function(beta, se, sim) {
   original <- exp(simulated) %>% # exponential = inverse of log
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est,
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   
@@ -52,12 +50,10 @@ logit_back <- function(beta, se, sim) {
   original <- plogis(simulated) %>% # invlogit
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -77,12 +73,10 @@ probit_back <- function(beta, se, sim) {
   original <- pnorm(simulated) %>% # inv-probit
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   
@@ -103,12 +97,10 @@ inverse_back <- function(beta, se, sim) {
   original <- 1 / simulated %>% # inverse
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -128,12 +120,10 @@ square_back <- function(beta, se, sim) {
   original <- sqrt(simulated) %>% # inverse of x^2
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   
@@ -154,12 +144,10 @@ cube_back <- function(beta, se, sim) {
   original <- pracma::nthroot(simulated, n = 3) %>% # inverse of x^3, use non-base to allow for -ve numbers
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -179,12 +167,10 @@ identity_back <- function(beta, se, sim) { # identity (typo) TODO
   original <- simulated %>% #  no transformation
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -205,12 +191,10 @@ power_back <- function(beta, se, sim, n) {
   original <- pracma::nthroot(simulated, n = n) %>% # inverse of x^n, use non-base to allow for -ve numbers
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est/ sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -231,8 +215,7 @@ divide_back <- function(beta, se, sim, n) {
   original <- simulated * n %>%
     na.omit()
   m_est <- mean(original, na.rm = TRUE)
-  sd_est <- sd(original, na.rm = TRUE)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original, na.rm = TRUE)
   quantiles <- quantile(original,
     c(0.025, 0.975),
     na.rm = TRUE
@@ -240,7 +223,6 @@ divide_back <- function(beta, se, sim, n) {
   set <- data.frame(
     mean_origin = m_est,
     se_origin = se_est,
-    sd_origin = sd_est,
     lower = quantiles[[1]],
     upper = quantiles[[2]]
   )
@@ -264,12 +246,10 @@ square_root_back <- function(beta, se, sim) {
   original <- simulated^2 %>%
     na.omit()
   m_est <- mean(original)
-  sd_est <- sd(original)
-  se_est <- sd_est / sqrt(length(original))
+  se_est <- sd(original)
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, 
                     se_origin = se_est, 
-                    sd_origin = sd_est,
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
diff --git a/R/conversion.R b/R/conversion.R
index bc84f58..2a05764 100644
--- a/R/conversion.R
+++ b/R/conversion.R
@@ -67,13 +67,16 @@ conversion <- function(beta, se, transformation, sim = 10000) {
     square_root_back(beta, se, sim)
   } else if (transformation == "(power3)/100") {
     x100 <- divide_back(beta, se, sim, 100)
-    cube_back(x100$mean_origin, x100$se_origin, sim = 1000)
+    cube_back(x100$mean_origin, x100$se_origin, sim)
   } else if (stringr::str_detect(transformation, "power")) {
     n <- str_split(transformation, "power") %>%
       pluck(1, 2) %>%
       as.numeric()
     if (rlang::is_na(n)) {
-      return(data.frame(mean_origin = NA, m_est = NA, se_origin = NA, sd_origin = NA, lower = NA, upper = NA))
+      return(data.frame(mean_origin = NA, 
+                        se_origin = NA, 
+                        lower = NA, 
+                        upper = NA))
     } else {
       power_back(beta, se, sim, n)
     }
@@ -82,12 +85,18 @@ conversion <- function(beta, se, transformation, sim = 10000) {
       pluck(1, 3) %>%
       as.numeric()
     if (rlang::is_na(n)) {
-      return(data.frame(mean_origin = NA, m_est = NA, se_origin = NA, sd_origin = NA, lower = NA, upper = NA))
+      return(data.frame(mean_origin = NA, 
+                        se_origin = NA, 
+                        lower = NA, 
+                        upper = NA))
     } else {
       divide_back(beta, se, sim, n)
     }
   } else if (transformation == "double_transformation") {
-    return(data.frame(mean_origin = NA, m_est = NA, se_origin = NA, sd_origin = NA, lower = NA, upper = NA))
+    return(data.frame(mean_origin = NA, 
+                      se_origin = NA, 
+                      lower = NA, 
+                      upper = NA))
   } else {
     identity_back(beta, se, sim) # TODO change conditional logic to ensure strange transformations not put through here
   }
diff --git a/R/log_transform.R b/R/log_transform.R
index c4adb21..12b61f0 100644
--- a/R/log_transform.R
+++ b/R/log_transform.R
@@ -19,13 +19,11 @@ log_transform <- function(estimate = numeric(1L),
     na.omit()
   
   m_est <- mean(log_simulated)
-  sd_est <- sd(log_simulated)
-  std.error_est <- sd_est / sqrt(length(log_simulated))
+  se_est <- sd(log_simulated)
   quantiles <- quantile(log_simulated, c(0.025, 0.975), na.rm = TRUE)
   
   out <- data.frame(mean_log = m_est, 
-                    se_log = std.error_est, 
-                    sd_log = sd_est,
+                    se_log = se_est, 
                     lower = quantiles[[1]], 
                     upper = quantiles[[2]])