We focus on the diagnostic ability assessment of medical tests when the outcome of interest is the status (alive or dead) of the subjects at a certain time-point t. This binary status is determined by right-censored times to event and it is unknown for those subjects censored before t. Here we provide three methods (unknown status exclusion, imputation of censored times and using time-dependent ROC curves) to evaluate the diagnostic ability of binary and continuous tests in this context. Two references for the methods used here are Skaltsa et al. (2010) <doi:10.1002/bimj.200900294> and Heagerty et al. (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.

Provides functions for the selection of thresholds for use in 
    extreme value models, based mainly on the methodology in 
    Northrop, Attalides and Jonathan (2017) <doi:10.1111/rssc.12159>.
    It also performs predictive inferences about future extreme values, 
    based either on a single threshold or on a weighted average of inferences 
    from multiple thresholds, using the 'revdbayes' package 
    <https://cran.r-project.org/package=revdbayes>.   
    At the moment only the case where the data can be treated as 
    independent identically distributed observations is considered.

Pure R implementation of Apache Thrift.
    This library doesn't require any code generation.
    To learn more about Thrift go to <https://thrift.apache.org>.

Provides threshold sweep methods for Qualitative Comparative 
    Analysis (QCA). Implements Condition Threshold Sweep-Single (CTS-S), 
    Condition Threshold Sweep-Multiple (CTS-M), Outcome Threshold Sweep (OTS), 
    and Dual Threshold Sweep (DTS) for systematic exploration of threshold 
    calibration effects on crisp-set QCA results. These methods extend 
    traditional robustness approaches by treating threshold variation as an 
    exploratory tool for discovering causal structures. Also provides Fiss 
    (2011) <doi:10.5465/amj.2011.60263120> core/peripheral condition 
    classification via compute_fiss_core() and generate_fiss_chart(), enabling 
    four-symbol configuration charts that distinguish core conditions (present 
    in both parsimonious and intermediate solutions) from peripheral conditions 
    (intermediate only). Built on top of the 'QCA' package by Dusa (2019) 
    <doi:10.1007/978-3-319-75668-4>, with function arguments following 'QCA' 
    conventions. Based on set-theoretic methods by Ragin (2008) 
    <doi:10.7208/chicago/9780226702797.001.0001> and established robustness 
    protocols by Oana and Schneider (2024) <doi:10.1177/00491241211036158>.
    This package supersedes 'TSQCA'; see the NEWS file for migration guidance.