我正在尝试基于两个条件在R中进行回归.我的数据具有年份和其他分类的二进制变量.仅使用1个条件,我就可以使回归正常运行:
I am trying to run a regression in R based on two conditions. My data has binary variables for both year and another classification. I can get the regression to run properly while only using 1 condition:
# now time for the millions of OLS # format: OLSABCD where ABCD are binary for the values of MSA/UA and years # A = 1 if MSA, 0 if UA # B = 1 if 2010 # C = 1 if 2000 # D = 1 if 1990 OLS1000<-summary(lm(lnrank ~ lnpop, data = subset(df, msa==1))) OLS1000但是,我无法弄清楚如何同时将MSA/UA分类与年份变量一起使用.我已经尝试过:
However I cannot figure out how to get both the MSA/UA classification to work with the year variables as well. I have tried:
OLS1100<-summary(lm(lnrank ~ lnpop, data = subset(df, msa==1, df$2010==1))) OLS1100但是它返回错误:
Error: unexpected numeric constant in "OLS1100<-summary(lm(lnrank ~ lnpop, data = subset(df, msa==1, df$2010"如何使程序在两种情况下都能运行?
How can I get the program to run utilizing both conditions?
再次感谢您!
推荐答案问题是:
df$2010如果您的数据确实有一个名为2010的列,那么您需要在其周围加上反引号:
If your data really has a column named 2010, then you need backticks around it:
df$`2010`在您的子集中,不要两次指定df:
And in your subset, don't specify df twice:
subset(df, msa == 1, `2010` == 1)通常,最好不要使用数字开头的列名.最好不要命名数据帧df,因为这是一个函数名.
In general it's better if column names don't start with digits. It's also best not to name data frames df, since that's a function name.
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