在R回归中循环不同的变量和数据集

# 假设我们有两个数据集 data1 和 data2，每个数据集有多个变量
data1 <- data.frame(y = c(1, 2, 3), x1 = c(4, 5, 6), x2 = c(7, 8, 9))
data2 <- data.frame(y = c(10, 11, 12), x1 = c(13, 14, 15), x2 = c(16, 17, 18))

# 定义一个函数来进行线性回归分析
run_regression <- function(data, response_var, predictor_vars) {
  formula <- as.formula(paste(response_var, "~", paste(predictor_vars, collapse = "+")))
  model <- lm(formula, data = data)
  return(summary(model))
}

# 定义变量和数据集的组合
combinations <- list(
  list(data = data1, response_var = "y", predictor_vars = c("x1")),
  list(data = data1, response_var = "y", predictor_vars = c("x2")),
  list(data = data2, response_var = "y", predictor_vars = c("x1", "x2"))
)

# 循环执行回归分析
results <- list()
for (i in seq_along(combinations)) {
  result <- run_regression(combinations[[i]]$data, combinations[[i]]$response_var, combinations[[i]]$predictor_vars)
  results[[i]] <- result
}

# 打印结果
for (i in seq_along(results)) {
  print(paste("Results for combination", i))
  print(results[[i]])
}