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I'm trying to create a stargazer table for a set of regressions, where I ran each regression on a subset of my data. The natural way to do this, I would think, is to use split to create a list of data.frames from my data, create a list of lm objects by using lapply on the list of data.frames, and then feed that list to stargazer. For example,

library(MASS)
library(stargazer)

data(Boston)

# This doesn't work
by.river <- split(Boston, Boston$chas)
fit <- lapply(by.river, lm, formula = crim ~ indus)
stargazer(fit, type = "text")

# % Error: Unrecognized object type.
# % Error: Unrecognized object type.

If I divide them up manually, this works fine:

# This works
fit2 <- vector(mode = "list", length = 2)
fit2[[1]] <- lm(crim ~ indus, data = Boston, subset = (chas == 0))
fit2[[2]] <- lm(crim ~ indus, data = Boston, subset = (chas == 1))
stargazer(fit2, type = "text")

But with my real data, the thing I'm splitting by has several values, and I would rather not split them all up by hand. Any ideas why I'm getting the "% Error: Unrecognized object type." error?

Jake Fisher
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    I really do not know why you (and now me as well) should be getting that error. The help page suggests that a list of model objects should be acceptable input. The only difference I can see between `fit` and `fit2` is that `fit` is numbered. – IRTFM Jan 13 '15 at 23:03
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    It might have something to do with how the lm object stores function calls. If you do `lapply(fit, summary)`, you get `Call: FUN(formula = ..1, data = X[[1L]])`, versus `lapply(fit2, summary)`, which gives `Call: lm(formula = crim ~ indus, data = Boston, subset = (chas == 0))`. But that's the closest I can figure out. – Jake Fisher Jan 14 '15 at 21:09
  • Very interesting. So the fit2 item are stored as calls but not evaluated until they are needed. Sounds like another effect of R's lazy evaluation mechanism. `stargazer` is then seeing an unevaluated expression and doesn't push it through the evaluation mechanism. It might be worth a note to the package maintainer. – IRTFM Jan 14 '15 at 21:18
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    Did anyone already this to the package maintainer? I believe that getting `lapply(formulas, lm, data=my.data)` working would be worthwhile. – chandler Sep 16 '16 at 09:06

1 Answers1

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There is an easy workaround, hinted at by BondedDust and suggested by careful perusal of the help for lapply. 

fit <- lapply(by.river, function(dd)lm(crim ~ indus,data=dd))
stargazer(fit, type = "text")
fit[[1]]$call
#lm(formula = crim ~ indus, data = dd)
atiretoo
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  • Too bad it doesn't work without the anonymous function, but this seems like a reasonable workaround. – Jake Fisher Sep 21 '15 at 00:48
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    It has to be something to do with how `stargazer` identifies the type of object. functions in package `AICcmodavg` are fine with lists of models created this way. – atiretoo Sep 21 '15 at 01:13