v1.6.0 release

v1.6.0 release, now including parallel functionality in smcfcs.parallel

v1.5.0 released

New functionality for discrete time survival analysis with missing covariates added.

v1.4.2 released

Version 1.4.2 includes functionality for automatically producing convergence plots using ggplot2.

smcfcs version 1.4.0

Adding functionality for covariates measured with classical covariate measurement error, when internal replicate measurements are available. Also adding Weibull substantive model functionality.

smcfcs version 1.3.1

Fixing bug in check of whether partially observed variables that need to be imputed have imputation methods specified and that methods are not specified for fully observed variables.

smcfcs version 1.3.0

This release adds two new functions, smcfcs.nestedcc and smcfcs.casecohort, which provide functionality for nested case control and case cohort study designs.

smcfcs version 1.2.1

This new minor release fixes a bug which was discovered which affected the drawing of posterior parameters values of the substantive model when the latter is linear regression.

smcfcs version 1.2.0

This new release adds functionality to accommodating Poisson substantive models for count outcomes.

smcfcs version 1.1.1

Version 1.1.1 - a number of small changes, plus critical bug fix for linear substantive models with categorical missing covariates. The bug which has been fixed meant that if the substantive model was linear regression, imputation of categorical covariates was done incorrectly.

smcfcs version 1.1.0

The main addition in version 1.1.0 of smcfcs is the ability to impute covariates with competing risks data. smcfcs assumes a Cox proportional hazards model for each competing cause of failure, and imputes covariates compatibly with these models.