Question

这是我的问题的简化版本，包含示例数据：

每年，我在院子里找到40个球。其中一定比例是红色的。我想随着时间的推移对红球的比例进行建模。

library(tidyverse)
library(modelr)

# generate some proportion data that changes by year
data = tibble(
  year = 2011:2020, 
  reds = 1:10, # red balls
  total = 40, # total number of balls
  propRed = reds / total # proportion of red balls each year
)

# fit to a model
model = glm(propRed ~ year, XXX_WHAT_GOES_HERE_XXX, data)

# graph the model's prediction and the data
tibble(year = 2000:2030) %>% 
  modelr::add_predictions(model, "propRed") %>% 
  ggplot() + 
    aes(y=propRed, x=year) + 
    geom_line() +
    geom_point(data=data)

Answer 1

我们可以使用cbind(successes, failures)的公式界面中的glm选项来使用逻辑回归：

model <- glm(cbind(reds, total - reds) ~ year, family = 'binomial', data = data)

tibble(year = 2000:2030) %>% 
    mutate(propRed = predict(model, newdata = ., type = 'response')) %>%
    ggplot() + 
    aes(y=propRed, x=year) + 
    geom_line() +
    geom_point(data=data)

使用比例因变量拟合数据

1 个答案: