impute {niaidMI} | R Documentation |
Multiple Imputation for NIAID-OS.
Description
Imputes NIAID OS data using a Markov model.
Usage
impute(
wide,
m,
by = NULL,
days = paste0("D", 1:28),
bin = rep(1, length(days) - 1),
Em = get_emission(wide, days),
listFormatOut = FALSE,
tol = 1e-06,
maxiter = 200,
silent = FALSE
)
Arguments
wide |
Data in wide format (i.e., each day is a column). |
m |
Number of imputations. |
by |
Character vector with column names. Data will be broken up and imputed separately for every combination of values for specified columns in the data. |
days |
Names of the columns that contain the score for each day. Columns should be in sequential order. |
bin |
The assigned bin for pooling together information across transitions. Must be a numeric vector of length=(length(days)-1). By default all transitions are pooled together. |
Em |
Emission probabilities. Generally the default should not be changed. |
listFormatOut |
Return each imputed dataset in a list or combine into a single dataset. |
tol |
Tolerance for relative reduction the log-likelihood to determine convergence of the Baum-Welch algorithm. |
maxiter |
Maximum iterations before stopping the EM algorithm. |
silent |
Allows silencing some messages. |
Details
States for each patient/day in 'wide' may be the following:
Not missing:An integer from 1 to 8.
Missing:NA
Partially Missing: Range which may be code as a characters string such as '[1,7]' or '[1,2]'. Such a character string indicates that while the actual value is unknown, it is known that the value falls within the specified range.
Value
If listFormatOut = TRUE, then a list will be returned with each element being an imputed data set. If listFormatOut = FALSE, then a single data.frame will be returned where IMP_ID column is created.
See Also
Examples
test <- sim_data(100)
bs <- impute(wide=test,m=2, by="strata", silent=TRUE)