I am new to RStudio and I guess my question is pretty easy to solve but a lot of searching did not help me.
I am running a regression and summary(regression1)
shows me all the coefficients and so on. Now I am using coef(regression1)
so it only gives me the coefficients which I want to export to a file.
write.csv(coef, file="regression1.csv)
and the "Error in as.data.frame.default(x[[i]], optional = TRUE) : cannot coerce class ""function"" to a data.frame"
occurs.
Would be great If you could help me. I am searching the web for a few hours now and was not successful.
Do I have to change coef
somehow so it fits in a data.frame?
Thank you very much!
This is r2, the Coefficient of Determination. It tells you how many points fall on the regression line. for example, 80% means that 80% of the variation of y-values around the mean are explained by the x-values.
There's a contributed package called broom
that simplifies this task, it converts model output to tidy dataframes. Here's a self-contained reproducible example:
Download and install the package:
library(devtools) install_github("dgrtwo/broom") library(broom)
Here's the normal base output, not very convenient:
lmfit <- lm(mpg ~ wt, mtcars) lmfit Call: lm(formula = mpg ~ wt, data = mtcars) Coefficients: (Intercept) wt 37.285 -5.344
Here's the same model output after it's been tidied up by the broom
package, much nicer and easier to work with:
tidy_lmfit <- tidy(lmfit) tidy_lmfit term estimate std.error statistic p.value 1 (Intercept) 37.285126 1.877627 19.857575 8.241799e-19 2 wt -5.344472 0.559101 -9.559044 1.293959e-10
And here's how you'd write that dataframe to CSV:
write.csv(tidy_lmfit, "tidy_lmfit.csv")
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