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| library(rio) | |
| library(janitor) | |
| pew <- import("E://data/atp99.sav") %>% clean_names() | |
| aaa1 <- pew %>% | |
| mutate(gene = genev2_w99) %>% | |
| mutate(gene = frcode(gene == 1 ~ "Good Idea", | |
| gene == 3 ~ "Not Sure", | |
| gene == 2 ~ "Bad Idea")) %>% | |
| ct(gene, wt = weight_w99, show_na = FALSE) %>% | |
| mutate(rel = "Entire Sample") | |
| aaa2 <- pew %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| mutate(gene = genev2_w99) %>% | |
| mutate(gene = frcode(gene == 1 ~ "Good Idea", | |
| gene == 3 ~ "Not Sure", | |
| gene == 2 ~ "Bad Idea")) %>% | |
| group_by(rel) %>% | |
| ct(gene, wt = weight_w99, show_na = FALSE) | |
| both <- bind_rows(aaa1, aaa2) %>% | |
| filter(rel != 'NA') %>% | |
| mutate( | |
| rel = factor(rel, levels = c("Entire Sample", "Evangelical Prot.", "Non-Evangelical", "Catholic", "Unaffiliated", "All Others")) | |
| ) | |
| both %>% | |
| mutate(lab = round(pct, 2)) %>% | |
| ggplot(., aes(x = 1, y = pct, fill = fct_rev(gene))) + | |
| geom_col(color = "black") + | |
| coord_flip() + | |
| facet_wrap(~ rel, ncol =1, strip.position = "left") + | |
| theme_rb() + | |
| scale_fill_manual(values = c("Good Idea" = "#1b9e77", "Not Sure" = "#d95f02", "Bad Idea" = "#7570b3")) + | |
| theme(legend.position = "bottom") + | |
| scale_y_continuous(labels = percent) + | |
| theme(strip.text.y.left = element_text(angle=0)) + | |
| guides(fill = guide_legend(reverse=T, nrow = 1)) + | |
| theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) + | |
| theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) + | |
| geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") + | |
| # geom_text(aes(label = ifelse(age2 == "18-35", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") + | |
| # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") + | |
| theme(plot.title = element_text(size = 16)) + | |
| theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) + | |
| theme(legend.text = element_text(size = 18)) + | |
| labs(x = "", y = "", title = "Do you think the widespread use of gene editing to greatly reduce a baby's risk\nof developing serious diseases or health conditions over their lifetime would be a...", | |
| caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 99, November 2021") | |
| save("gene_edit_all.png", wd = 9, ht = 4.5) | |
| aaa1 <- pew %>% | |
| mutate(gene = genev3_w99) %>% | |
| mutate(gene = frcode(gene == 1 ~ "Yes, Definitely", | |
| gene == 2 ~ "Yes, Probably", | |
| gene == 3 ~ "No, Probably Not", | |
| gene == 4 ~ "No, Definitely Not")) %>% | |
| ct(gene, wt = weight_w99, show_na = FALSE) %>% | |
| mutate(rel = "Entire Sample") | |
| aaa2 <- pew %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| mutate(gene = genev3_w99) %>% | |
| mutate(gene = frcode(gene == 1 ~ "Yes, Definitely", | |
| gene == 2 ~ "Yes, Probably", | |
| gene == 3 ~ "No, Probably Not", | |
| gene == 4 ~ "No, Definitely Not")) %>% | |
| group_by(rel) %>% | |
| ct(gene, wt = weight_w99, show_na = FALSE) | |
| both <- bind_rows(aaa1, aaa2) %>% | |
| filter(rel != 'NA') %>% | |
| mutate( | |
| rel = factor(rel, levels = c("Entire Sample", "Evangelical Prot.", "Non-Evangelical", "Catholic", "Unaffiliated", "All Others")) | |
| ) | |
| both %>% | |
| mutate(lab = round(pct, 2)) %>% | |
| ggplot(., aes(x = 1, y = pct, fill = fct_rev(gene))) + | |
| geom_col(color = "black") + | |
| coord_flip() + | |
| facet_wrap(~ rel, ncol =1, strip.position = "left") + | |
| theme_rb() + | |
| scale_fill_manual(values = c( | |
| "Yes, Definitely" = "#1b9e77", # Teal green | |
| "Yes, Probably" = "#66c2a5", # Light teal | |
| "No, Probably Not" = "#fc8d62", # Orange | |
| "No, Definitely Not" = "#d53e4f" # Red | |
| )) + | |
| theme(legend.position = "bottom") + | |
| scale_y_continuous(labels = percent) + | |
| theme(strip.text.y.left = element_text(angle=0)) + | |
| guides(fill = guide_legend(reverse=T, nrow = 1)) + | |
| theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) + | |
| theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) + | |
| geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") + | |
| # geom_text(aes(label = ifelse(age2 == "18-35", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") + | |
| # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") + | |
| theme(plot.title = element_text(size = 16)) + | |
| theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) + | |
| theme(legend.text = element_text(size = 16)) + | |
| labs(x = "", y = "", title = "If gene editing to greatly reduce a baby's risk of developing serious diseases or health\nconditions over their lifetime were available, is this something you would want?", | |
| caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 99, November 2021") | |
| save("gene_edit_all_your_baby.png", wd = 9, ht = 4.5) | |
| aaa1 <- pew %>% | |
| mutate(better = genev4_b_w99) %>% | |
| mutate(better = case_when(better == 1 | better == 2 ~ 1, | |
| better == 3 | better == 4 ~ 0)) %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| group_by(rel) %>% | |
| mean_ci(better, wt = weight_w99, ci = .84) %>% | |
| mutate(type = "Gene Editing Would Help People Live Longer and Better Lives") | |
| aaa2 <- pew %>% | |
| mutate(better = genev4_c_w99) %>% | |
| mutate(better = case_when(better == 1 | better == 2 ~ 1, | |
| better == 3 | better == 4 ~ 0)) %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| group_by(rel) %>% | |
| mean_ci(better, wt = weight_w99, ci = .84) %>% | |
| mutate(type = "Gene Editing Would Lead to Medical Advances for Society") | |
| aaa3 <- pew %>% | |
| mutate(better = genev4_d_w99) %>% | |
| mutate(better = case_when(better == 1 | better == 2 ~ 1, | |
| better == 3 | better == 4 ~ 0)) %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| group_by(rel) %>% | |
| mean_ci(better, wt = weight_w99, ci = .84) %>% | |
| mutate(type = "Gene Editing Would Would Go Too Far in Eliminating Natural Differences") | |
| all <- bind_rows(aaa1, aaa2, aaa3) %>% filter(rel != "NA") | |
| all %>% | |
| ggplot(., aes(x = fct_rev(rel), y = mean, fill = rel)) + | |
| geom_col(color = "black") + | |
| theme_rb() + | |
| coord_flip() + | |
| error_bar() + | |
| y_pct() + | |
| scale_fill_manual(values = c( | |
| "Evangelical Prot." = "#1b9e77", # Teal | |
| "Non-Evangelical" = "#7570b3", # Purple | |
| "Catholic" = "#d95f02", # Orange | |
| "Unaffiliated" = "#e7298a", # Pink | |
| "All Others" = "#66a61e" # Green | |
| )) + | |
| lab_bar(above = FALSE, type = mean, pos = .035, sz = 7) + | |
| facet_wrap(~ type, ncol = 1) + | |
| labs(x = "", y = "", title = "What Are Some Possible Implications of Gene Editing?", | |
| caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 99, November 2021") | |
| save("gene_editing_implications.png", ht = 8, wd = 8) | |
| library(dplyr) | |
| library(broom) | |
| library(jtools) # for plot_coefs | |
| library(ggplot2) | |
| pew_clean <- pew %>% | |
| mutate( | |
| gene = case_when(genev3_w99 == 4 ~ 1, | |
| genev3_w99 %in% 1:3 ~ 0), | |
| rel = frcode( | |
| f_religcat1 == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| f_religcat1 == 1 & f_born == 2 ~ "Non-Evangelical", | |
| f_religcat1 == 2 ~ "Catholic" | |
| ), | |
| attend = 7 - f_attend, | |
| republican = if_else(i_partyid == 1, 1, 0), | |
| white = if_else(i_race == 1, 1, 0), | |
| male = if_else(i_gender == 1, 1, 0), | |
| age = f_agecat, | |
| educ = f_educcat2 | |
| ) %>% | |
| filter(!is.na(rel), !is.na(gene), !is.na(attend), !is.na(republican), | |
| !is.na(white), !is.na(male), !is.na(age), !is.na(educ)) | |
| mod_evangelical <- glm(gene ~ attend + republican + white + male + age + educ, | |
| data = filter(pew_clean, rel == "Evangelical Prot."), | |
| family = binomial) | |
| mod_nonevan <- glm(gene ~ attend + republican + white + male + age + educ, | |
| data = filter(pew_clean, rel == "Non-Evangelical"), | |
| family = binomial) | |
| mod_catholic <- glm(gene ~ attend + republican + white + male + age + educ, | |
| data = filter(pew_clean, rel == "Catholic"), | |
| family = binomial) | |
| coef_names <- c("White" = "white", | |
| "Education" = "educ", | |
| "Age" = "age", | |
| "Male" = "male", | |
| "Republican" = "republican", | |
| "No Religion" = "none", | |
| "Attendance" = "attend") | |
| library(jtools) | |
| plot_coefs(mod_evangelical, mod_nonevan, mod_catholic, | |
| model.names = c("Evangelical", "Non-Evangelical", "Catholic"), | |
| include = ".*", # show all terms | |
| scale = TRUE, | |
| coefs = coef_names) + | |
| labs(title = "Predicting What Factors Lead to a Complete Refusal to Gene Editing for Serious Disease", | |
| x = "Log-Odds (Standardized)", | |
| y = NULL) + | |
| theme_rb() + | |
| add_text(x = .5, y = 4.5, word = "Definitely Wouldn't Gene Edit", sz = 7) + | |
| theme(legend.position = c(0.25, 0.85), # top right corner, inside plot | |
| legend.justification = c("right", "top"), | |
| legend.background = element_rect(fill = "white", color = "black")) | |
| save("regression_gene_editing.png") | |
| gg <- pew %>% | |
| mutate(rel = f_religcat1) %>% | |
| mutate(rel = frcode(rel == 1 & f_born == 1 ~ "Evangelical Prot.", | |
| rel == 1 & f_born == 2 ~ "Non-Evangelical", | |
| rel == 2 ~ "Catholic", | |
| rel == 3 ~ "Unaffiliated", | |
| rel == 4 ~ "All Others")) %>% | |
| mutate(age = frcode(f_agecat == 1 ~ "18-29", | |
| f_agecat == 2 ~ "30-49", | |
| f_agecat == 3 ~ "50-64", | |
| f_agecat == 4 ~ "65+")) %>% | |
| mutate(gene = case_when(genev3_w99 == 4 ~ 1, | |
| genev3_w99 %in% 1:3 ~ 0)) %>% | |
| group_by(rel, age) %>% | |
| mean_ci(gene, wt = weight_w99, ci = .84) %>% filter(age != "NA") %>% filter(rel != "NA") | |
| gg %>% | |
| ggplot(., aes(x = age, y = mean, fill = rel)) + | |
| geom_col(color = "black") + | |
| facet_wrap(~ rel) + | |
| scale_fill_manual(values = c( | |
| "Evangelical Prot." = "#1b9e77", # Teal | |
| "Non-Evangelical" = "#7570b3", # Purple | |
| "Catholic" = "#d95f02", # Orange | |
| "Unaffiliated" = "#e7298a", # Pink | |
| "All Others" = "#66a61e" # Green | |
| )) + | |
| theme_rb() + | |
| error_bar() + | |
| y_pct() + | |
| lab_bar_white(above = FALSE, type = mean, pos = .03, sz = 6) + | |
| labs(x = "Age of Respondent", y = "", title = "Share Who Would Definitely Not Use Gene Editing to Reduce Risk\nof Baby Developing a Serious Disease", | |
| caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 99, November 2021") | |
| save("age_gene_editing.png", ht = 8, wd = 7) |
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