06_jointpoint.Rmd

# Joinpoint 联结点回归模型

```{r setup, include=FALSE}
options(digits = 4, 
        dplyr.print_min = 6, 
        dplyr.print_max = 6,
        htmltools.dir.version = FALSE, 
        formatR.indent = 2, 
        width = 55
        )

knitr::opts_chunk$set(
                      echo = TRUE, 
                      warning = FALSE, 
                      message = FALSE,
                      fig.width = 6, 
                      fig.height = 4,
                      fig.showtext = TRUE
                      )
library(tidyverse)
library(ggplot2)
library(readxl)
library(showtext)
library(sf)
```


## 实战-数据处理

```{r eval=FALSE}
# 读取并查看数据
df <- read.csv("data/Global_HIV.csv",header = T)
colnames(df)
unique(df$measure)
unique(df$location)
unique(df$sex)
unique(df$age)
unique(df$cause)
unique(df$metric)
unique(df$year)
```

```{r eval=FALSE}
# 筛选数据：
number <- df |> 
  filter(cause%in%c("HIV/AIDS","Syphilis","Chlamydial infection",
                    "Gonococcal infection","Trichomoniasis",
                    "Genital herpes")) |> 
  filter(age=="All ages") |> 
  filter(metric=="Number") |> 
  filter(measure=="Incidence") |> 
  mutate(val=round(val,0),    #将数据变为整数
         upper=round(upper,0),
         lower=round(lower,0)) |> 
  arrange(cause,sex,year)    #重排序，非常重要


ASR <- df |> 
  filter(cause%in%c("HIV/AIDS","Syphilis","Chlamydial infection",
                    "Gonococcal infection","Trichomoniasis",
                    "Genital herpes")) |> 
  filter(age=="Age-standardized") |> 
  filter(measure=="Incidence") |> 
  filter(metric=="Rate") |> 
  mutate(se=(upper-lower)/(2*1.96)) |>  #生成se
  arrange(cause,sex,year)    #重排序，非常重要
```

```{r eval=FALSE}
# 写出数据
write.csv(number,"data/number.csv",row.names = F)
write.csv(ASR,"data/ASR.csv",row.names = F)
```











```{r intro-ds-1, out.width = '90%', fig.align='center', echo = FALSE}
knitr::include_graphics("images/050z.png", dpi = 300)
```