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2022_12_02.R
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## ----setup, include=FALSE, message=FALSE-----------------------------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
library(pacman)
`%notin%` <- Negate(`%in%`)
p_load(
#--- Packages to Fit Models
MASS, logistf, survival, pROC, fastR2, broom.mixed, lmerTest,
#--- Packages to Produce Tables
table1, gtsummary, flextable, janitor, broom, officer, kableExtra, reactable,latex2exp,
#--- Packages to Produce Figures
ggsci, ggridges, ggthemes, ggforce, ggpubr, patchwork,
grid, gridExtra, plotly, survminer, viridis, ggridges,
hrbrthemes, stickylabeller,
#--- Packages for Data Retrieval & Pre-Processing
readxl, here, rdrop2, lubridate, zoo, tidyverse, purrr, data.table, stringr, haven, stringr
)
library(pacman)
`%notin%` <- Negate(`%in%`)
p_load(
#--- Packages to Fit Models
MASS, logistf, survival,
#--- Packages to Produce Tables
gtsummary, flextable, janitor, broom, officer, kableExtra, reactable,
#--- Packages to Produce Figures
crayon, ggsci, ggridges, ggthemes, ggforce, ggpubr, patchwork, grid, gridExtra, plotly, survminer, viridis, ggridges, hrbrthemes, stickylabeller, latex2exp, scales, glue,
#--- Packages for Data Retrieval & Pre-Processing
readxl, here, rdrop2, lubridate, zoo, tidyverse, purrr, data.table, stringr, tidyr, table1
)
y <- read_csv(file.path(here(), "data", "created_data", "2022_11_21.csv")) %>%
group_by(Customer) %>%
summarise(tid = unique(Customer), total = n(), late = sum(!is.na(lateFees))) %>%
select(tid, total, late) %>%
rename(n_total = "total",
n_late = "late")
covariates <- read_csv(file.path(here(), "data", "created_data", "2022_07_31.csv")) %>%
rename(age = "Age on effective date of action",
sex = "Sex",
n_hh = "Total number in household",
n_dep = "Number of dependents",
n_br = "Number of bedrooms in unit",
income = "Adjusted annual income: 8a minus 8x (if 8x is larger, put 0)",
rent = "Tenant rent: 10d minus 10en If positive or 0, put tenant rent If negative, credit tenant") %>%
select(c(tid, age, sex, n_hh, n_dep, n_br, income, rent))
## some weird duplication issue, dropping duplicates for now
covariates <- covariates %>%
filter(tid %notin%
(covariates %>% group_by(tid) %>% summarise(n = n()) %>% filter(n > 1) %>% pull(tid)))
buildings <- read_csv(file.path(here(), "data", "created_data", "2022_03_21.csv")) %>%
select(c(tid, name, late_duration, late_amount))
data <- covariates %>% inner_join(y) %>% inner_join(buildings) %>% rowwise() %>%
mutate(n_hh = case_when(n_hh > 3 ~ factor("> 3", levels = c("1", "2", "3", "> 3")),
TRUE ~ factor(n_hh, levels = c("1", "2", "3", "> 3"))),
n_dep = case_when(TRUE ~ factor(n_dep, levels = c("0", "1", "2"))),
n_br = case_when(n_br >= 3 ~ factor(">=3", levels = c("1", "2", ">=3")),
TRUE ~ factor(n_br, levels = c("1", "2", ">=3"))))
data <- data %>% drop_na() %>%
rowwise() %>%
mutate(prop = wilson.ci(x = n_late, n = n_total, conf.level = 0.50)[1]) %>%
mutate(prop = case_when(prop < 0 ~ 0,
prop > 1 ~ 1,
TRUE ~ prop))
## ----table1, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center'------------------------------------
label(data$sex) <- "Sex"
label(data$age) <- "Age"
units(data$age) <- "years"
label(data$income) <- "Income"
units(data$income) <- "$"
label(data$n_hh) <- "# in household"
label(data$n_dep) <- "# of dependents"
label(data$n_br) <- "# of bedrooms"
label(data$prop) <- "Proportion of late payment"
#label(melanoma2$ulcer) <- "Ulceration"
#label(melanoma2$thickness) <- "Thickness"
#units(melanoma2$thickness) <- "mm"
table1(~ age + sex + n_hh + n_dep + n_br + income + prop| name, data %>% drop_na(),
render.continuous = c(.="Mean (SD)",
.="Median (IQR)",
.="[Min, Max]"))
## ----fig1, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
ggplot(aes(y = name, x = age, fill = name)) +
geom_violin(width=1.4) +
geom_boxplot(width=0.1, color="black") +
theme_bw() +
xlab("Age (years)") +
ylab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "Building")
## ----fig2, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
filter(income <= 30000) %>%
ggplot(aes(y = name, x = income, fill = name)) +
geom_violin(width=1.4) +
geom_boxplot(width=0.1, color="black") +
theme_bw() +
xlab("Annual income ($)") +
ylab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "Building")
## ----fig3, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
group_by(name, sex) %>%
summarize(n = n()) %>%
ungroup() %>%
drop_na() %>%
ggplot(aes(fill = sex, x = name, y = n)) +
geom_bar(position="fill", stat="identity") +
theme_bw() +
ylab("Fraction") +
xlab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "Sex") +
coord_flip()
## ----fig4, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
group_by(name, n_hh) %>%
summarize(n = n()) %>%
ungroup() %>%
drop_na() %>%
ggplot(aes(fill = n_hh, x = name, y = n)) +
geom_bar(position="fill", stat="identity") +
theme_bw() +
ylab("Fraction") +
xlab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "# in household") +
coord_flip()
## ----fig5, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
group_by(name, n_dep) %>%
summarize(n = n()) %>%
ungroup() %>%
drop_na() %>%
ggplot(aes(fill = n_dep, x = name, y = n)) +
geom_bar(position="fill", stat="identity") +
theme_bw() +
ylab("Fraction") +
xlab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "# of dependents") +
coord_flip()
## ----fig6, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
group_by(name, n_br) %>%
summarize(n = n()) %>%
ungroup() %>%
drop_na() %>%
ggplot(aes(fill = n_br, x = name, y = n)) +
geom_bar(position="fill", stat="identity") +
theme_bw() +
ylab("Fraction") +
xlab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "# of bedrooms") +
coord_flip()
## ----fig7, echo = FALSE, warning=FALSE, message=FALSE, fig.align='center', fig.height=10, fig.width=15---------
data %>%
ggplot(aes(y = name, x = prop, fill = name)) +
geom_violin(width=1.4) +
geom_boxplot(width=0.1, color="black") +
theme_bw() +
xlab("Proportion of lateness") +
ylab("") +
theme(legend.position = "bottom",
legend.box="vertical", legend.margin=margin(),
axis.text.x = element_text(face = "bold", size = 18),
axis.text.y = element_text(face = "bold", size = 18),
plot.title = element_text(face = "bold", size = 18),
plot.subtitle = element_text(size = 14),
#axis.text = element_text(size = 12),
axis.title = element_text(face = "bold", size = 18),
legend.title = element_text(face = "bold", size = 18),
legend.text = element_text(size = 18)) +
labs(fill = "Building")
## ----prop_age, echo=FALSE, messages=FALSE, warning=FALSE-------------------------------------------------------
op <- tidy(lmer(prop ~ -1 + age + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)
## ----prop_sex, echo=FALSE, messages=FALSE, warning=FALSE-------------------------------------------------------
op <- tidy(lmer(prop ~ sex + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)
## ----prop_numDep, echo=FALSE, messages=FALSE, warning=FALSE----------------------------------------------------
op <- tidy(lmer(prop ~ n_dep + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)
## ----prop_numBed, echo=FALSE, messages=FALSE, warning=FALSE----------------------------------------------------
op <- tidy(lmer(prop ~ n_br + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)
## ----prop_income, echo=FALSE, messages=FALSE, warning=FALSE----------------------------------------------------
op <- tidy(lmer(prop ~ rent + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)
## ----prop_all, echo=FALSE, messages=FALSE, warning=FALSE-------------------------------------------------------
op <- tidy(lmer(prop ~ age + sex + n_dep + rent + (1 | name), data = data))
op[-c(nrow(op)-1, nrow(op)), ] %>% kbl() %>% kable_paper("hover", full_width = T)