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Performs reference-based multiple imputation

doRefBasedMI.Rd

Creates multiple imputations using RefBasedMI, based on the dataset and relevant options specified by a call to proposeMI. If a substantive model is specified, also calculates the pooled estimates using pool.

Usage

doRefBasedMI(
  mipropobj,
  covs,
  depvar,
  treatvar,
  idvar,
  method,
  reference,
  seed,
  substmod = " ",
  message = TRUE
)

Arguments

mipropobj

An object of type 'miprop', created by a call to 'proposeMI'

covs

The analysis model covariate(s), specified as a string (space delimited)

depvar

The longitudinal outcome variable(s), specified as a string (space delimited)

treatvar

Numeric treatment group variable; values must be positive integers

idvar

Participant identifier variable

method

Reference-based imputation method; methods that are supported are "J2R", "CR", and "CIR"

reference

Numeric reference group for the specified method

seed

An integer that is used to set the seed of the 'mice' call

substmod

Optionally, a symbolic description of the substantive model to be fitted, specified as a string; if supplied, the model will be fitted to each imputed dataset and the results pooled

message

If TRUE (the default), displays a message summarising the analysis that has been performed; use message = FALSE to suppress the message

Value

A 'mice' object of class 'mids' (the multiply imputed datasets). Optionally, a message summarising the analysis that has been performed.

Details

The dataset is assumed to be in 'wide' format. Data are assumed to be multivariate normal within each treatment arm. See RefBasedMI for further details.

Examples

if (FALSE) { # interactive()
# First specify the imputation model as a 'mimod' object
## (suppressing the message)
mimod_qol12 <- checkModSpec(formula="qol12 ~ factor(group) + age0 + qol0 + qol3",
                           family="gaussian(identity)",
                           data=qol,
                           message=FALSE)
# Save the proposed 'mice' options as a 'miprop' object
## (suppressing the message)
miprop_qol12 <- proposeMI(mimodobj=mimod_qol12,
                    data=qol,
                    message=FALSE,
                    plot = FALSE)
# Create the set of imputed datasets using the proposed 'mice' options and
## specified reference-based imputation method; then, fit the substantive
## model to each imputed dataset and display the pooled results
doRefBasedMI(mipropobj=miprop_qol12, covs="age0 qol0",
             depvar="qol3 qol12", treatvar="group",
             idvar="id", method="J2R", reference=1, seed=123,
             substmod = "lm(qol12 ~ factor(group) + age0 + qol0)")
}