Package: basecamb 1.1.5

J. Peter Marquardt

basecamb: Utilities for Streamlined Data Import, Imputation and Modelling

Provides functions streamlining the data analysis workflow: Outsourcing data import, renaming and type casting to a *.csv. Manipulating imputed datasets and fitting models on them. Summarizing models.

Authors:J. Peter Marquardt [aut, cre], Till D. Best [aut]

basecamb_1.1.5.tar.gz
basecamb_1.1.5.zip(r-4.7)basecamb_1.1.5.zip(r-4.6)basecamb_1.1.5.zip(r-4.5)
basecamb_1.1.5.tgz(r-4.6-any)basecamb_1.1.5.tgz(r-4.5-any)
basecamb_1.1.5.tar.gz(r-4.7-any)basecamb_1.1.5.tar.gz(r-4.6-any)
basecamb_1.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
basecamb/json (API)

# Install 'basecamb' in R:

install.packages('basecamb', repos = c('https://codeblue-team.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/codeblue-team/basecamb/issues

On CRAN:

3.73 score 3 stars 1 packages 12 scripts 729 downloads 17 exports 105 dependencies

Last updated from:41360a34ab. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	182
source / vignettes	OK	201
linux-release-x86_64	OK	177
macos-release-arm64	OK	127
macos-oldrel-arm64	OK	116
windows-devel	OK	129
windows-release	OK	135
windows-oldrel	OK	116
wasm-release	OK	149

Exports:apply_data_dictionary apply_function_to_imputed_data assign_factorial_levels assign_types_names build_model_formula cox.zph.mids deconstruct_formula filter_nth_entry fit_mult_impute_obs_outcome or_model_summary parse_date_columns quantile_group remove_duplicates remove_missing_from_mids scale_continuous_predictors setduplicates stratified_boxcox

Dependencies:assertthat backports base64enc bit bit64 boot broom bslib cachem checkmate cli clipr cluster codetools colorspace cpp11 crayon data.table digest dplyr evaluate farver fastmap fontawesome forcats foreach foreign Formula fs generics ggplot2 glmnet glue gridExtra gtable haven highr Hmisc hms htmlTable htmltools htmlwidgets isoband iterators jomo jquerylib jsonlite knitr labeling lattice lifecycle lme4 magrittr MASS Matrix memoise mice mime minqa mitml nlme nloptr nnet numDeriv ordinal pan pillar pkgconfig prettyunits progress purrr R6 rappdirs rbibutils RColorBrewer Rcpp RcppEigen Rdpack readr reformulas rlang rmarkdown rpart rstudioapi S7 sae sass scales shape stringi stringr survival tibble tidyr tidyselect tinytex tzdb ucminf utf8 vctrs viridisLite vroom withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Scaling a variable	.scale_variable
Clean column names, types and levels	apply_data_dictionary
Apply function to dataframes in a mice object	apply_function_to_imputed_data
Assign custom values for key levels in factorial columns	assign_factorial_levels
Assign tidy types and names to a data.frame	assign_types_names
Build formula for statistical models	build_model_formula
Test cox proportional odds assumption on models using multiple imputation.	cox.zph.mids
Deconstruct formula	deconstruct_formula
Filter dataframe for nth entry	filter_nth_entry
Fit a model on multiply imputed data using only observations with non-missing outcome(s)	fit_mult_impute_obs_outcome
Summarise a logistic regression model on the odds ratio scale	or_model_summary
Parse values in date columns as Dates	parse_date_columns
Stratify a numeric vector into quantile groups	quantile_group
Remove duplicate rows from data.frame	remove_duplicates
Remove missing cases from a mids object	remove_missing_from_mids
Scale continuous predictors	scale_continuous_predictors
Identify duplicate values in a vector representing a set	setduplicates
Box-Cox transformation for stratified data	stratified_boxcox