Comments (1)
You may create your own imputation method by defining a function whose name starts with mice.impute.
, for example something like
mice.impute.myfunc <- function(y, ry, x, ...) {your code here}
The myfunc
part is just a placeholder, so mice.impute.banana()
is also valid. Then mice(..., method = "banana")
call will use mice.impute.banana()
method instead of the standard function. Bottom line: you may evade this error by defining a function with the name mice.impute.myfunc
in your active workspace.
from mice.
Related Issues (20)
- Reference table of predictor matrix codes
- Error in colMeans(as.matrix(imp[[j]]), na.rm = TRUE) : 'x' must be numeric HOT 4
- Default behavior of `make.predictorMatrix()` outputs `1`s for complete variables HOT 2
- Accidentally repeated roxygen comments HOT 3
- Add `cluster` argument to `make.method()` and `make.predictorMatrix()`
- ampute.discrete failing when input data set contains character/categorical variables HOT 1
- pooling parameters df_error = "Inf" HOT 1
- pool() on lavaan objects gives error: illegal arguments passed to lavaan::parameterEstimates HOT 1
- pool() on lavaan fit objects gives error: coef() not available on S4 object HOT 2
- Add cluster variable to `ampute()` for multilevel amputation
- Change reference level in logistic regression following MI using MICE HOT 2
- Chi square tests following multiple imputation
- mice::ampute() not working properly when adding character variables HOT 1
- futuremice error with blocks - possibly due to how ibind deals with blocked imputations
- mice doesn't handle complex variable names
- `method` argument of `mice` ignores variable names? HOT 2
- `quickpred()` errors when `minpuc` is a vector or matrix
- `Error: object 'mice.impute.2l.pmm' not found` when using `futuremice()` HOT 1
- parlmice progress bar HOT 2
- Different results within mice compared to directly using method functions HOT 1
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from mice.