CLIP.confint.difflevel {nncc} | R Documentation |
logistf
after multiple imputationThe function was modified from [CLIP.confint](https://CRAN.R-project.org/package=logistf/index.html])
to combine
results from m imputed data sets that have different structures (e.g., a
covariate in a model have different levels across different imputed data
sets) on April 15, 2022.
CLIP.confint.difflevel(
obj = NULL,
variable = NULL,
data,
firth = TRUE,
weightvar = NULL,
control = logistf.control(),
ci.level = c(0.025, 0.975),
pvalue = TRUE,
offset = NULL,
bound.lo = NULL,
bound.up = NULL,
legacy = FALSE
)
obj |
Either a list of logistf fits (on multiple imputed data sets), or the result of analysis of a |
variable |
Must be used to include variables of interest; each of variable of interest must have the same levels across different imputed data sets. |
data |
A list of data set corresponding to the model fits. Can be left blank if obj was obtained with the |
firth |
If |
weightvar |
An optional weighting variable for each observation. |
control |
Control parameters for |
ci.level |
The two confidence levels for each tail of the posterior distribution. |
pvalue |
If |
offset |
An optional offset variable |
bound.lo |
Bounds (vector of length 2) for the lower limit. Can be left blank. Use only if problems are encountered. |
bound.up |
Bounds (vector of length 2) for the upper limit. Can be left blank. Use only if problems are encountered. |
legacy |
If |
The formula in [logistf](https://CRAN.R-project.org/package=logistf/index.html])
must be written as variable of
interest followed by covariates that have different levels across different
imputed data sets.
For more information, please refer to the vignette using
browseVignettes("nncc")
and the original function
[CLIP.confint](https://CRAN.R-project.org/package=logistf/index.html])
.
Please cite the original function [CLIP.confint](https://CRAN.R-project.org/package=logistf/index.html])
for
publication.
An object of class CLIP.confint
, with items:
variable |
The variable(s) which were analyzed |
estimate |
The pooled estimate (average over imputations) |
ci |
The confidence interval(s) |
pvalue |
The p-value(s) |
imputations |
The number of imputed datasets |
ci.level |
The confidence level (input) |
bound.lo |
The bounds used for finding the lower confidence limit; usually not of interest. May be useful for error-tracing. |
bound.up |
The bounds used for finding the upper confidence limit |
iter |
The number of iterations (for each variable and each tail) |
call |
The call object |