- version: get the current mice version
- data/exampledata: get example data by its name
- data: upload a csv to the HTTP server, retrieve a hash
data_token
to reuse the data - long: long format of the imputed data
- fit
- pool
The function mice
takes a lot of different arguments.
Required arguments:
- data: full path to a csv file, name of an example dataset in the mice package or a hash from the data endpoint
- maxit: as defined in mice, integer number
- m: as defined in mice, integer number
- seed: as defined in mice, integer number
The endpoint returns mice:complete(, "long", include = TRUE)
; the return value includes the original data to be compatible with the fit endpoint.
Optional input arguments:
- predictorMatrix: a list of numbers of length columns x columns; a matrix of size columns x columns;
Example (3 variables/columns):
"predictorMatrix": [[0,1,1,1],[1,0,1,1],[1,1,0,1],[1,1,1,0]]
- blocks: a json dictionary (in R a named list) mapping variables to blocks of variables;
Example:
"blocks": {"b1": ["chl", "hyp"], "b2": ["bmi"]}
- parcel: see blocks
- ignore: a list of length number of rows with the values true or false
Example:
"ignore":[true,true,true,true,true,true,true,true,true,true,true,true,true,true, true,false,false,false,false,false,false,false,false,false,false]
- where: a list of length rows x columns, or a matrix of the same size as the data, of values true and false
Example:
"where":[[false,true,true,true],[false,false,false,false],[false,true,false,false], [false,true,true,true],[false,false,false,false],[false,true,true,false], [false,false,false,false],[false,false,false,false],[false,false,false,false], [false,true,true,true],[false,true,true,true],[false,true,true,true], [false,false,false,false],[false,false,false,false],[false,false,false,true], [false,true,true,true],[false,false,false,false],[false,false,false,false], [false,false,false,false],[false,false,false,true],[false,true,true,true], [false,false,false,false],[false,false,false,false],[false,false,false,true], [false,false,false,false]]
-
"visitSeq": visitSequence, a vector of variable or parcel/block names
Example:
"visitSeq":["a","b"]
- "method": a list of strings to describe the method how to impute the variable
Example:
"method":["","pmm","pmm","pmm"]
- "formulas": a list of strings which describe formulas
Example:
"formulas":["bmi ~ age", "bmi ~ hyp"]
- "dots": a named list of with for each parcel (optionally) a list of arguments to pass down optional arguments to lower level imputation functions.
Example:
"dots":{"age":{"donor":20}}