DESCRIPTION

Package: miPredict
Type: Package
Title: Predictive models from multiply imputed data
Version: 0.2.6
Date: 2023-05-04
Authors@R: person("Peter", "Humburg", email = "p.humburg@unsw.edu.au",
                  role = c("aut", "cre"))
Maintainer: Peter Humburg <p.humburg@unsw.edu.au>
Description: Variable selection and model fitting for predictive
    (generalized linear) models from multiply imputed data.
    The focus is on logistic regression models with some support
    for other GLMs.
Depends: R (>= 3.6.0)
Imports: mice, glmnet, glmnetUtils, dplyr, ggplot2, fmsb, pROC, stringr, tidyr, methods, rlang, generalhoslem, forcats, SpecsVerification, purrr, stats, classifierplots
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Collate: 
    'boot_model.R'
    'call_imputed.R'
    'candidate_models.R'
    'class_perf.R'
    'clean_data.R'
    'crossvalidate.R'
    'fit_model.R'
    'hoslem.R'
    'internals.R'
    'makeglm.r'
    'pool_r2.R'
    'pool_cor.R'
    'performance.R'
    'plot.R'
    'pool_auc.R'
    'pool_brier.R'
    'pool_hoslem.R'
    'pool_model.R'
    'pool_predictions.R'
    'pool_roc.R'
    'predict_outcome.R'
    'scale_data.R'
    'select_model.R'
    'select_variables.R'
Suggests: 
    testthat (>= 2.1.0)