问题
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
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
But it returns the error:
Error: unexpected numeric constant in "OLS1100<-summary(lm(lnrank ~ lnpop,
data = subset(df, msa==1, df$2010"
How can I get the program to run utilizing both conditions?
Thank you again!
回答1:
The problem is:
df$2010
If your data really has a column named 2010, then you need backticks around it:
df$`2010`
And in your subset, don't specify df twice:
subset(df, msa == 1, `2010` == 1)
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.
回答2:
@neilfws pointed out the "numeric as column names issue", but there is actually another issue in your code.
The third argument of subset() is actually reserved for the select =, which lets you choose which columns to include (or exclude). So the correct syntax should be:
subset(df, msa == 1 & `2010` == 1)
instead of
subset(df, msa == 1, `2010` == 1)
This second code would not give you an error, but it also would not give you the right condition.
来源：https://stackoverflow.com/questions/42499760/r-conditional-regression-with-multiple-conditions