diff --git a/R/back_transformations.R b/R/back_transformations.R
index 93e1ce3..097a775 100644
--- a/R/back_transformations.R
+++ b/R/back_transformations.R
@@ -21,7 +21,7 @@ log <- function(beta, se, sim) {
   original <- exp(simulated) %>% # exponential = inverse of log
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -40,7 +40,7 @@ logit <- function(beta, se, sim) {
   original <- plogis(simulated) %>% # invlogit
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -59,7 +59,7 @@ probit <- function(beta, se, sim) {
   original <- pnorm(simulated) %>% # inv-probit
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -78,7 +78,7 @@ inverse <- function(beta, se, sim) {
   original <- 1 / simulated %>% # inverse
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -97,7 +97,7 @@ square <- function(beta, se, sim) {
   original <- sqrt(simulated) %>% # inverse of x^2
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -116,7 +116,7 @@ cube <- 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)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -135,7 +135,7 @@ identity <- function(beta, se, sim) { # identity (typo) TODO
   original <- simulated %>% #  no transformation
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -155,7 +155,7 @@ power <- 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)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%
@@ -175,7 +175,7 @@ divide <- function(beta, se, sim, n) {
   original <- simulated * n %>%
     na.omit()
   m_est <- mean(original, na.rm = TRUE)
-  se_est <- sd(original, na.rm = TRUE)/sqrt(length(original))
+  se_est <- sd(original, na.rm = TRUE) / sqrt(length(original))
   quantiles <- quantile(original,
     c(0.025, 0.975),
     na.rm = TRUE
@@ -205,7 +205,7 @@ square_root <- function(beta, se, sim) {
   original <- simulated^2 %>%
     na.omit()
   m_est <- mean(original)
-  se_est <- sd(original)/sqrt(length(original))
+  se_est <- sd(original) / sqrt(length(original))
   quantiles <- quantile(original, c(0.025, 0.975), na.rm = TRUE)
   set <- data.frame(mean_origin = m_est, se_origin = se_est, lower = quantiles[[1]], upper = quantiles[[2]])
   if (flatten_dbl(set) %>%