Provides a collection of intuitive and user-friendly functions
    for computing confidence intervals for common statistical tasks, including
    means, differences in means, proportions, and odds ratios. The package also
    includes tools for linear regression analysis and several real-world datasets
    intended for teaching and applied statistical inference.

Read data from 'LimeSurvey'
    (<https://www.limesurvey.org/>)
    in a comfortable way.
    Heavily inspired by 'limer'
    (<https://github.com/cloudyr/limer/>),
    which lacked a few comfort features for me.

An R client for the 'ipbase.com' IP Geolocation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://ipbase.com/docs> .

Provides tools for passing messages between R processes. 
    Shiny examples are provided showing how to perform useful tasks such as: 
    updating reactive values from within a future, progress bars for long running 
    async tasks, and interrupting async tasks based on user input.

We propose the inverse probability-of-censoring weighted (IPCW) Kendall's tau to measure the association of the survival trait with biomarkers and Kendall's partial correlation to reflect the relationship of the survival trait with interaction variable conditional on main effects, as described in Wang and Chen (2020) <doi:10.1093/bioinformatics/btaa017>.

Performs valid statistical inference on predicted data (IPD) using recent methods, where for a subset of the data, the outcomes have been predicted by an algorithm. Provides a wrapper function with specified defaults for the type of model and method to be used for estimation and inference. Further provides methods for tidying and summarizing results. Salerno et al., (2024) <doi:10.48550/arXiv.2410.09665>.

An implementation to reconstruct individual patient data from Kaplan-Meier (K-M) survival curves, visualize and assess the accuracy of the reconstruction, then perform secondary analysis on the reconstructed data. We involve a simple function to extract the coordinates form the published K-M curves. The function is developed based on Poisot T. ’s digitize package (2011)  <doi:10.32614/RJ-2011-004> . For more complex and tangled together graphs, digitizing software, such as 'DigitizeIt' (for MAC or windows) or 'ScanIt'(for windows) can be used to get the coordinates. Additional information should also be involved to increase the accuracy, like numbers of patients at risk (often reported at 5-10 time points under the x-axis of the K-M graph), total number of patients, and total number of events. The package implements the modified iterative K-M estimation algorithm (modified-iKM) improved upon the approach proposed by Guyot (2012) <doi:10.1186/1471-2288-12-9> with some modifications.