R 来自一张表的两个回归
我试图通过划分数据将两条不同的回归线（公式为：salary = beta0 + beta1D3 + beta2spending + beta3*(spending*D3) + w）绘制成一个散点图分为两个子集，如以下代码所示：
salary = data$salary
spending = data$spending
D1 = data$North
D2 = data$South
D3 = data$West
subsetWest = subset(data, D3 == 1)
subsetRest = subset(data, D3 == 0)
abab = lm(salary ~ 1 + spending + 1*spending, data=subsetWest) #red line
caca = lm(salary ~ 0 + spending + 0*spending, data=subsetRest) #blue line
plot(spending,salary)
points(subsetWest$spending, subsetWest$salary, pch=25, col = "red")
points(subsetRest$spending, subsetRest$salary, pch=10, col = "blue")
abline(abab, col = "red")
abline(caca, col = "blue")
这是我的数据表的示例：
这是是运行代码时得到的图：
[在此处输入图像描述][2] [2]：https://i.sstatic.net/It8ai.png
我的问题是我的第二个回归的截距是错误的，事实上我与第一次回归不同，在查看摘要时甚至没有得到截距。
有人知道我的问题出在哪里吗？或者有人知道绘制两条回归线的替代方法吗？
非常感谢您的帮助。非常感谢！
这是整个表：
structure(list(salary = c(39166L, 40526L, 40650L, 53600L, 58940L,
53220L, 61356L, 54340L, 51706L, 49000L, 48548L, 54340L, 60336L,
53050L, 54720L, 43380L, 43948L, 41632L, 36190L, 41878L, 45288L,
49248L, 54372L, 67980L, 46764L, 41254L, 45590L, 43140L, 44160L,
44500L, 41880L, 43600L, 45868L, 36886L, 39076L, 40920L, 42838L,
50320L, 44964L, 41938L, 54448L, 51784L, 45288L, 49280L, 44682L,
51220L, 52030L, 51576L, 58264L, 51690L), spending = c(6692L,
6228L, 7108L, 9284L, 9338L, 9776L, 11420L, 11072L, 8336L, 7094L,
6318L, 7242L, 7564L, 8494L, 7964L, 7136L, 6310L, 6118L, 5934L,
6570L, 7828L, 9034L, 8698L, 10040L, 7188L, 5642L, 6732L, 5840L,
5960L, 7462L, 5706L, 5066L, 5458L, 4610L, 5284L, 6248L, 5504L,
6858L, 7894L, 5018L, 10880L, 8084L, 6804L, 5658L, 4594L, 5864L,
7410L, 8246L, 7216L, 7532L), North = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), South = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L), West = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L)), class = "data.frame", row.names = c(NA,
-50L))
I am trying to plot two different regression lines (with the formula: salary = beta0 + beta1D3 + beta2spending + beta3*(spending*D3) + w) into one scatter plot by deviding the data I have into two subsets as seen in the following code:
salary = data$salary
spending = data$spending
D1 = data$North
D2 = data$South
D3 = data$West
subsetWest = subset(data, D3 == 1)
subsetRest = subset(data, D3 == 0)
abab = lm(salary ~ 1 + spending + 1*spending, data=subsetWest) #red line
caca = lm(salary ~ 0 + spending + 0*spending, data=subsetRest) #blue line
plot(spending,salary)
points(subsetWest$spending, subsetWest$salary, pch=25, col = "red")
points(subsetRest$spending, subsetRest$salary, pch=10, col = "blue")
abline(abab, col = "red")
abline(caca, col = "blue")
This is a sample of my data table:
And this is the plot I get when running the code:
[enter image description here][2] [2]: https://i.sstatic.net/It8ai.png
My problem is that the intercept for my second regression is wrong, in fact I do not even get an intercept when looking at the summary, unlike with the first regression.
Does anybody see where my problem is or does anybody know an alternative way of plotting the two regression lines?
Help would be much appreciated. Thank you very much!
This is the whole table:
structure(list(salary = c(39166L, 40526L, 40650L, 53600L, 58940L,
53220L, 61356L, 54340L, 51706L, 49000L, 48548L, 54340L, 60336L,
53050L, 54720L, 43380L, 43948L, 41632L, 36190L, 41878L, 45288L,
49248L, 54372L, 67980L, 46764L, 41254L, 45590L, 43140L, 44160L,
44500L, 41880L, 43600L, 45868L, 36886L, 39076L, 40920L, 42838L,
50320L, 44964L, 41938L, 54448L, 51784L, 45288L, 49280L, 44682L,
51220L, 52030L, 51576L, 58264L, 51690L), spending = c(6692L,
6228L, 7108L, 9284L, 9338L, 9776L, 11420L, 11072L, 8336L, 7094L,
6318L, 7242L, 7564L, 8494L, 7964L, 7136L, 6310L, 6118L, 5934L,
6570L, 7828L, 9034L, 8698L, 10040L, 7188L, 5642L, 6732L, 5840L,
5960L, 7462L, 5706L, 5066L, 5458L, 4610L, 5284L, 6248L, 5504L,
6858L, 7894L, 5018L, 10880L, 8084L, 6804L, 5658L, 4594L, 5864L,
7410L, 8246L, 7216L, 7532L), North = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), South = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L), West = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L)), class = "data.frame", row.names = c(NA,
-50L))
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这是因为您的第二个模型没有指定拦截，因为您使用
... ~ 0 + ...另外，您的第一个模型没有意义，因为它包含
spending两次。spending的第二个条目将被lm忽略That is because your second model specifies no intercept, since you use
... ~ 0 + ...Also, your first model doesn't make sense because it includes
spendingtwice. The second entry forspendingwill be ignored bylm