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basecamb

Biomedical Applications of Statistical Evaluation - Coding Assets by Marquardt and Best

Overview

basecamb is a collection of utilities for streamlined data analysis including multiple imputation and model fitting.

Installation

basecamb is under active development. You can install either from CRAN or get the current development version from GitHub.

# The easiest way to get basecmab is installing it from CRAN
install.packages("basecamb")

# Altenatively, you can get the development version from GitHub:
# install.packages("devtools")
devtools::install_github("codeblue-team/basecamb")

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Version

Install

install.packages('basecamb')

Monthly Downloads

823

Version

1.1.2

License

GPL (>= 3)

Issues

1

Pull Requests

0

Stars

3

Forks

0

Maintainer

J. Marquardt

Last Published

March 11th, 2023

Functions in basecamb (1.1.2)

or_model_summary

Summarise a logistic regression model on the odds ratio scale
parse_date_columns

Parse values in date columns as Dates
filter_nth_entry

Filter dataframe for nth entry
scale_continuous_predictors

Scale continuous predictors
quantile_group

Stratify a numeric vector into quantile groups
remove_missing_from_mids

Remove missing cases from a mids object
fit_mult_impute_obs_outcome

Fit a model on multiply imputed data using only observations with non-missing outcome(s)
.parse_string_to_named_vector

Parse a string to create a named list
assign_factorial_levels

Assign custom values for key levels in factorial columns
assign_types_names

Assign tidy types and names to a data.frame
.scale_variable

Scaling a variable
build_model_formula

Build formula for statistical models
cox.zph.mids

Test cox proportional odds assumption on models using multiple imputation.
.find_NA_coercions

Locate NA values introduced during apply_data_dictionary()
deconstruct_formula

Deconstruct formula
apply_function_to_imputed_data

Apply function to dataframes in a mice object
apply_data_dictionary

Clean column names, types and levels