This is a problem of using different names between your data and your newdata and not a problem between using vectors or dataframes.

When you fit a model with the lm function and then use predict to make predictions, predict tries to find the same names on your newdata. In your first case name x conflicts with mtcars$wt and hence you get the warning.

See here an illustration of what I say:

This is what you did and didn't get an error:

a <- mtcars$mpg
x <- mtcars$wt

#here you use x as a name
fitCar <- lm(a ~ x) 
#here you use x again as a name in newdata.
predict(fitCar, data.frame(x = mean(x)), interval = "confidence") 

       fit      lwr      upr
1 20.09062 18.99098 21.19027

See that in this case you fit your model using the name x and also predict using the name x in your newdata. This way you get no warnings and it is what you expect.

Let's see what happens when I change the name to something else when I fit the model:

a <- mtcars$mpg
#name it b this time
b <- mtcars$wt 

fitCar <- lm(a ~ b) 
#here I am using name x as previously
predict(fitCar, data.frame(x = mean(x)), interval = "confidence") 

         fit       lwr      upr
1  23.282611 21.988668 24.57655
2  21.919770 20.752751 23.08679
3  24.885952 23.383008 26.38890
4  20.102650 19.003004 21.20230
5  18.900144 17.771469 20.02882
Warning message:
'newdata' had 1 row but variables found have 32 rows 

The only thing I did now was to change the name x when fitting the model to b and then predict using the name x in the newdata. As you can see I got the same error as in your question.

Hope this is clear now!

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A way around this without making names is to use the following:

fitCar<-lm(mpg ~ wt, mtcars) #here you use x as a name
predict(fitCar,data.frame(wt=mean(mtcars$wt)), interval="confidence") 

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In the formula for lm function do not refer to the variables using the datasetname$variablename pattern. Instead use variablename + variablename ...This will not throw the warning: 'newdata' had nrow(test) row but variables found have nrow(train) rows.

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I got the same problem when I was using variable name in conjuction with data name with the use of $ sign.

So instead of:

fitCar<-lm(mtcars$mpg~mtcars$wt)
predict(fitCar,
        data.frame(x=mean(mtcars$wt)),
        interval="confidence")

Use this:

fitCar<-lm(mpg~wt , data = mtcars)
predict(fitCar,  
wt = mean(mtcars$wt), interval = "confidence")

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Comments

• And why come I get the same error in this case? install.packages("car") library(car) data(Quartet) lmfit = lm(Quartet$y2 ~ poly(Quartet$x,2,raw=TRUE)) newdata = data.frame(x = c(3,6,15)) predict(lmfit, newdata, interval = "confidence", level = 0.95)
• @agaved One your case since you re using the full Quartet$x name predict will also look for this in the newdata. As there is no Quartet$x in newdata but only newdata$x it fails.
• @agaved Also, if you have a new question please ask it as a new one. Do not use comments to ask different questions. This is a different problem than the one mentioned in the question.
• In the latter of the two cases described in this answer, what is R doing? Why does it give five lines of output?