NEWS.md
In xsswang/remiod: Reference-Based Multiple Imputation for Ordinal/Binary Response
remiod 1.0.1
New features
Ordinal Probit Model: new model option under algorithm='jags'. The option
can be requested with argument models = 'opm' (or named vectors, for example,
models = c(y1='opm',y2='opm')). algorithm='tang_seq': computation is speed up.get_subset: function is exported for extracting specified set of parameters
from MCMC samples. The extracted samples have a class of 'mcmc', and can be
directly used by functions/packages which take a 'mcmc' object.
Minor improvements and bug fixes
- Bug fix: when using a J2R imputation of continuous outcome through GLM
with
family = gaussian() using JAGS.
xsswang/remiod documentation built on Feb. 20, 2023, 9:29 a.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
remiod 1.0.1
New features
Ordinal Probit Model: new model option underalgorithm='jags'. The option can be requested with argumentmodels = 'opm'(or named vectors, for example,models = c(y1='opm',y2='opm')).algorithm='tang_seq': computation is speed up.get_subset: function is exported for extracting specified set of parameters from MCMC samples. The extracted samples have a class of 'mcmc', and can be directly used by functions/packages which take a 'mcmc' object.
Minor improvements and bug fixes
- Bug fix: when using a J2R imputation of continuous outcome through GLM
with
family = gaussian()using JAGS.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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