计算泊松回归系数的置信区间 [英] calculating confidence interval of coefficient in poisson regression

问题描述

泊松回归在我的 R 代码中如下所示:

The poisson regression looks as follows in My R-code:

poissmod <- glm(aerobics$y ~ factor(aerobics$x1) + factor(aerobics$x2) + aerobics$x3 + aerobics$x4, family = poisson)
poissmod

现在我必须计算因子 aerobics$x1 的置信区间(在没有 aerobics$x1 的模型中，因为这并不重要).

Now I have to compute a confidence interval for the factor aerobics$x1 (in a model without aerobics$x1 since this is not significant).

这可能看起来很简单，但我对 R 不熟悉，而且我在任何地方都找不到答案...

This might look very easy, but I am not familiar with R and I can 't find the answer anywhere...

谁能帮帮我?

非常感谢！

推荐答案

参见例如MASS 包中的 confint 函数 (http://stat.ethz.ch/R-manual/R-devel/library/MASS/html/confint.html):

See e.g. the confint function in the MASS package (http://stat.ethz.ch/R-manual/R-devel/library/MASS/html/confint.html):

ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg0 <- glm(SF ~ sex + ldose - 1, family = binomial)
confint(budworm.lg0)
confint(budworm.lg0, "ldose")

该示例适用于逻辑回归，但这也适用于泊松回归.

The example is for a logistic regression, but this will also work for a poisson regression.

这是 stats 包文档中关于泊松回归的另一个示例 (https://stat.ethz.ch/R-manual/R-devel/library/stats/html/confint.html):

Here is another example from the stats package documentation for a poisson regression (https://stat.ethz.ch/R-manual/R-devel/library/stats/html/confint.html):

## from example(glm)
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3, 1, 9); treatment <- gl(3, 3)
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
confint(glm.D93) # needs MASS to be present on the system
confint.default(glm.D93)  # based on asymptotic normality

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