Initial commit

Author: behrman

AgePeriodCohort/births_tv.Rmd

@@ -111,14 +111,14 @@ v %>%
 A helper function to set the mortality rates for all years to that of a given year.
 
 ```{r}
-set_rates <- function(.data, rate_year) {
-  .data %>% 
+set_rates <- function(data, rate_year) {
+  data %>% 
     left_join(
-      .data %>% 
+      data %>% 
         filter(year == rate_year) %>% 
         mutate(rate = deaths / population * 1e5) %>% 
         select(!c(year, deaths, population)),
-      by = names(.data) %>% setdiff(c("year", "deaths", "population"))
+      by = names(data) %>% setdiff(c("year", "deaths", "population"))
     )
 }
 ```
@@ -160,13 +160,13 @@ From 1999 to 2013, the unadjusted mortality rate increased from 382 to 415 death
 A helper function to add the weights for age adjustment.
 
 ```{r}
-add_weight <- function(.data, weight_year) {
-  .data %>% 
+add_weight <- function(data, weight_year) {
+  data %>% 
     left_join(
-      .data %>%
+      data %>%
         filter(year == weight_year) %>% 
         select(!c(year, deaths), weight = population),
-      by = names(.data) %>% setdiff(c("year", "deaths", "population"))
+      by = names(data) %>% setdiff(c("year", "deaths", "population"))
     )
 }
 ```

AgePeriodCohort/births_tv.md

@@ -1,7 +1,7 @@
 Regression and Other Stories: AgePeriodCohort
 ================
 Andrew Gelman, Jennifer Hill, Aki Vehtari
-2021-04-20
+2021-06-23
 
 -   [2 Data and measurement](#2-data-and-measurement)
     -   [2.4 Data and adjustment: trends in mortality
@@ -136,14 +136,14 @@ A helper function to set the mortality rates for all years to that of a
 given year.
 
 ``` r
-set_rates <- function(.data, rate_year) {
-  .data %>% 
+set_rates <- function(data, rate_year) {
+  data %>% 
     left_join(
-      .data %>% 
+      data %>% 
         filter(year == rate_year) %>% 
         mutate(rate = deaths / population * 1e5) %>% 
         select(!c(year, deaths, population)),
-      by = names(.data) %>% setdiff(c("year", "deaths", "population"))
+      by = names(data) %>% setdiff(c("year", "deaths", "population"))
     )
 }
 ```
@@ -193,13 +193,13 @@ substantial role in the increase of the unadjusted mortality.
 A helper function to add the weights for age adjustment.
 
 ``` r
-add_weight <- function(.data, weight_year) {
-  .data %>% 
+add_weight <- function(data, weight_year) {
+  data %>% 
     left_join(
-      .data %>%
+      data %>%
         filter(year == weight_year) %>% 
         select(!c(year, deaths), weight = population),
-      by = names(.data) %>% setdiff(c("year", "deaths", "population"))
+      by = names(data) %>% setdiff(c("year", "deaths", "population"))
     )
 }
 ```

Arsenic/arsenic_logistic_residuals_tv.Rmd

@@ -134,8 +134,8 @@ binned_means <- function(x, y, n_bins = 40) {
 Plot binned residuals.
 
 ```{r}
-plot_binned_residuals <- function(.data) {
-  .data %>% 
+plot_binned_residuals <- function(data) {
+  data %>% 
     ggplot(aes(x_mean)) +
     geom_hline(yintercept = 0, color = "white", size = 2) +
     geom_line(aes(y = 2 * y_se), color = "grey60") +

Arsenic/arsenic_logistic_residuals_tv.md

@@ -1,7 +1,7 @@
 Regression and Other Stories: Arsenic model residuals
 ================
 Andrew Gelman, Jennifer Hill, Aki Vehtari
-2021-04-20
+2021-06-23
 
 -   [14 Working with logistic
     regression](#14-working-with-logistic-regression)
@@ -193,8 +193,8 @@ binned_means <- function(x, y, n_bins = 40) {
 Plot binned residuals.
 
 ``` r
-plot_binned_residuals <- function(.data) {
-  .data %>% 
+plot_binned_residuals <- function(data) {
+  data %>% 
     ggplot(aes(x_mean)) +
     geom_hline(yintercept = 0, color = "white", size = 2) +
     geom_line(aes(y = 2 * y_se), color = "grey60") +

Arsenic/arsenic_logistic_residuals_tv_files/figure-gfm/unnamed-chunk-10-1.png

@@ -49,8 +49,8 @@ plot_coef <- function(fit, prob_outer = 1, xlim = NULL) {
     theme(text = element_text(family = "sans"))
 }
   # Plot implied prior and Bayesian R^2 distributions
-plot_r2 <- function(.data) {
-  .data %>% 
+plot_r2 <- function(data) {
+  data %>% 
     pivot_longer(cols = everything()) %>% 
     ggplot(aes(value)) +
     geom_histogram(binwidth = 0.01, boundary = 0) +

Arsenic/arsenic_logistic_residuals_tv_files/figure-gfm/unnamed-chunk-11-1.png

@@ -1,7 +1,7 @@
 Regression and Other Stories: Student
 ================
 Andrew Gelman, Jennifer Hill, Aki Vehtari
-2021-04-20
+2021-06-23
 
 -   [12 Transformations and
     regression](#12-transformations-and-regression)
@@ -51,8 +51,8 @@ plot_coef <- function(fit, prob_outer = 1, xlim = NULL) {
     theme(text = element_text(family = "sans"))
 }
   # Plot implied prior and Bayesian R^2 distributions
-plot_r2 <- function(.data) {
-  .data %>% 
+plot_r2 <- function(data) {
+  data %>% 
     pivot_longer(cols = everything()) %>% 
     ggplot(aes(value)) +
     geom_histogram(binwidth = 0.01, boundary = 0) +