Parameters from multiply imputed repeated analyses
Format models of class mira, obtained from mice::width.mids().
## S3 method for class 'mira' model_parameters( model, ci = 0.95, exponentiate = FALSE, p_adjust = NULL, verbose = TRUE, ... )
model |
An object of class |
ci |
Confidence Interval (CI) level. Default to 0.95 (95%). |
exponentiate |
Logical, indicating whether or not to exponentiate the
the coefficients (and related confidence intervals). This is typical for,
say, logistic regressions, or more generally speaking: for models with log
or logit link. Note: standard errors are also transformed (by
multiplying the standard errors with the exponentiated coefficients), to
mimic behaviour of other software packages, such as Stata. For
|
p_adjust |
Character vector, if not |
verbose |
Toggle warnings and messages. |
... |
Arguments passed to or from other methods. |
model_parameters() for objects of class mira works
similar to summary(mice::pool()), i.e. it generates the pooled summary
of multiple imputed repeated regression analyses.
library(parameters)
if (require("mice", quietly = TRUE)) {
data(nhanes2)
imp <- mice(nhanes2)
fit <- with(data = imp, exp = lm(bmi ~ age + hyp + chl))
model_parameters(fit)
}
## Not run:
# model_parameters() also works for models that have no "tidy"-method in mice
if (require("mice", quietly = TRUE) && require("gee", quietly = TRUE)) {
data(warpbreaks)
set.seed(1234)
warpbreaks$tension[sample(1:nrow(warpbreaks), size = 10)] <- NA
imp <- mice(warpbreaks)
fit <- with(data = imp, expr = gee(breaks ~ tension, id = wool))
# does not work:
# summary(pool(fit))
model_parameters(fit)
}
## End(Not run)
# and it works with pooled results
if (require("mice")) {
data("nhanes2")
imp <- mice(nhanes2)
fit <- with(data = imp, exp = lm(bmi ~ age + hyp + chl))
pooled <- pool(fit)
model_parameters(pooled)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.