Need some assistance in R. I ran the lm function and assigned it to variable. Then I used that variable to retrieve summary using pool() function.
Here's the code but getting argument data is missing. I saw same example but didn't get that error.
> modelFit1 <- with(imputed,lm(MPG ~ CYLINDERS+SIZE+HP+WEIGHT+ACCEL+ENG_TYPE))
> summary(pool(modelFit1))
Error in pool(modelFit1) : argument "data" is missing, with no default
Appreciate any help. Thanks.
I also had this error. In my case it was due to conflicting packages. I had loaded packages: "mice" and "mi", and "mitools", among others. There is no 'data' argument necessary for 'pool' in the "mice" package, but mi::pool does require a data argument. If you are using mice and following examples in mice's documentation, Try
pooled <- mice::pool(modelFit1))
summary(pooled)
Related
I'm getting a strange error when I run an lmer function in r.
I've tried changing the variable types (all of them are numeric or factor) and removing the NA before analysis, but nothing seems to work.
model_1 <- lmer(Q14 ~ gender * time + (1|OMID), data=data)
summary(model_1)
Specifically, my error message reads:
Error in as(value, fieldClass, strict = FALSE) :
internal problem in as(): “labelled” is(object, "numeric") is TRUE, but the metadata asserts that the 'is' relation is FALSE
Not sure why this is happening, but I can't seem to find any answers for it. Any help would be appreciated.
Thanks!
I think lmer has a problem with 'labelled' data. If you un-label the predictors it should work fine.
I had the same error: the code for the lme-formula worked perfectly fine and one day I encountered that error. The solution in my case was simply to restart the R session, reload the data - in my case from SPSS via library("haven")::read.sps and after that load library("lme4") and execute the lme-formula.
So, if the formula worked before without any error, maybe just clean the project environment and re-run the most crucial code without any additional packages loaded. Maybe it's just some "cross-contamination" between packages or an unwanted effect of any package on the dataframe.
I am having trouble getting the pairs() function to work in nlme. Take this example from Pinhiero and Bates Mixed-Effects Models in S and S-Plus.
The model itself runs just fine
fm1Theo.lis <- nlsList(conc ~ SSfol(Dose, Time, lKe, lKa, lCl), data = Theoph)
But the pairs plot...
pairs(fm1Theo.lis, id = 0.1)
...returns this error
Error in as.data.frame.default(x) :
cannot coerce class "c("nlsList", "lmList")" to a data.frame
I also tried
pairs(fm1Theo.lis, ~ ranef(., level = 2), id = 0.1)
But get the same error. Any ideas?
Here's how one may think in this case. The error
Error in as.data.frame.default(x) :
cannot coerce class ‘c("nlsList", "lmList")’ to a data.frame
says that some object of class c("nlsList", "lmList") is being coerced to a data frame. Now since fm1Theo.lis is the result of using nlsList, it seems that the object in the error is indeed nlsList. That means that pairs does not know what to do with objects of such class. To confirm this, we can run
pairs.default(fm1Theo.lis, id = 0.1)
which is what is going to happen when no specific method for fm1Theo.lis is found. Indeed the error is the same. In one way or another confirming that nlsList and comes from nlme, it becomes clear that the issue is with loading the nlme package. Loading it or restarting the session then is almost surely going to help.
I'm running the following code:
dat1 <- returns
for (j in 1:12) set(dat1, j = j, value = wind(dat1[[j]]))
And getting the following error message:
Error in wind(dat1[[j]]) : could not find function "wind"
My search for a solution mainly involves packages that aren't properly installed. I'm not 100% sure but I think it isn't related to that.
Best
To check if the function is really loaded into the namespace you have to try to
print the function:
print(wind)
Error in print(wind) : object 'wind' not found
You have to look if the package is correctly loaded
library("foo")
Check package dependency in case of error.
I use the findFn-function in sos-package to search for function names. Unfortunately dataset names also appear in the same column:
install.packages("sos")
library(sos)
findFn("wind")
There is a wind function (or dataset name) in packages: gstat, ismev, NPCirc, BAMBI, ggmap, gcookbook, CircOutlier, plotly, and circular.
Goal: mas5 normalize data.
Problem: when I try the following R code, I get this
error: unable to find an inherited method for function bg.correct for signature ExpressionFeatureSet, character
I have looked on SO, and found the following: What does this mean: unable to find an inherited method for function ‘A’ for signature ‘"B"’, but I am not exactly sure how to fix my specific problem and use the mas5 function properly. I have also looked at this affy manual but still stuck...
installpkg("affy")
library('affy')
setwd("/Users/er/Desktop/DesktopFolders/DataSets/CD8Helios/Microarray/CELfiles/CEL")
cel_Files <- list.celfiles()
affyRaw <- read.celfiles(cel_Files)
eset <- mas5(affyRaw)
If you are sure that the .cel files were created based on experiments performed on the type of array that works with affy package than you should try this workflow using ReadAffy from affy package.
cel_Files <- list.celfiles()
affyRaw <- affy::ReadAffy(filenames=cel_Files)
eset <- mas5(affyRaw)
However, it might be the case that the affy package is not designed for your array type. Then, you should switch to the oligo and oligoClasses packages and normalize with analogous function rma
cel_Files <- oligoClasses::list.celfiles()
affyRaw <- oligo::read.celfiles(cel_Files)
eset <- oligo::rma(affyRaw)
library(mice)
md.pattern(dat1)
temp<-mice(dat1, m = 5, seed = 101)
dat1 <- complete(temp, 2)
Error in UseMethod("complete_") :
no applicable method for 'complete_' applied to an object of class "mids"
Hi, I'm trying to impute missing values using mice package.
But I got the above error message.
The first time I imputed missing data it worked, but when I tried again it didn't. I've tried a lot with different options (changing seed, deleting existing data or "temp" variable)
Sometimes it worked but other times it didn't.
What is the problem and solution?
Thanks in advance.
I think the problem here is that you should rather be using some other libraries in your program which have a function named "complete". Just typing "complete" in help menu gave me 2 other libraries (tidyr,RCurl) which have the function in the same name. As simon suggested, I tried using "mice::complete". It works for me.
Try this:
dat1<-mice::complete(temp,2)
mice 3.7.5 redefines the complete() function as the S3 complete.mids() method for the generic tidyr::complete().
Assuming that mice is attached, you should no longer see no applicable method for 'complete_' applied to an object of class "mids".