midoc (version 1.0.0)

checkCRA: Inspect complete records analysis model

Description

Check complete records analysis is valid under the proposed analysis model and directed acyclic graph (DAG). Validity means that the proposed approach will allow unbiased estimation of the estimand(s) of interest, including regression parameters, associations, and causal effects.

Usage

checkCRA(y, covs, r_cra, mdag)

Value

A message indicating whether complete records analysis is valid under the proposed DAG and analysis model outcome and covariate(s)

Arguments

y

The analysis model outcome, specified as a string

covs

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

r_cra

The complete record indicator, specified as a string

mdag

The DAG, specified as a string using dagitty syntax

Details

The DAG should include all observed and unobserved variables related to the analysis model variables and their missingness, as well as all required missingness indicators.

In general, complete records analysis is valid if the analysis model outcome and complete record indicator are unrelated, conditional on the specified covariates. This is determined using the proposed DAG by checking whether the analysis model and complete record indicator are 'd-separated', given the covariates.

References

Hughes R, Heron J, Sterne J, Tilling K. 2019. Accounting for missing data in statistical analyses: multiple imputation is not always the answer. Int J Epidemiol. doi:10.1093/ije/dyz032

Bartlett JW, Harel O, Carpenter JR. 2015. Asymptotically Unbiased Estimation of Exposure Odds Ratios in Complete Records Logistic Regression. Am J Epidemiol. doi:10.1093/aje/kwv114

Examples

# Example DAG for which complete records analysis is not valid, but could be
## valid for a different set of covariates
checkCRA(y="bmi7", covs="matage", r_cra="r",
         mdag="matage -> bmi7 mated -> matage mated -> bmi7
               sep_unmeas -> mated sep_unmeas -> r")
# For the DAG in the example above, complete records analysis is valid
## if a different set of covariates is used
checkCRA(y="bmi7", covs="matage mated", r_cra="r",
         mdag="matage -> bmi7 mated -> matage mated -> bmi7
               sep_unmeas -> mated sep_unmeas -> r")

# Example DAG for which complete records is not valid, but could be valid
## for a different estimand
checkCRA(y="bmi7", covs="matage mated", r_cra="r",
         mdag="matage -> bmi7 mated -> matage mated -> bmi7
               sep_unmeas -> mated sep_unmeas -> r matage -> bmi3
               mated -> bmi3 bmi3 -> bmi7 bmi3 -> r")

# Example DAG for which complete records analysis is never valid
checkCRA(y="bmi7", covs="matage mated", r_cra="r",
         mdag="matage -> bmi7 mated -> matage mated -> bmi7
               sep_unmeas -> mated sep_unmeas -> r bmi7 -> r")