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compareCstat - Compare C-Statistics with Bootstrapped Confidence Intervals

Provides a function to compare C-statistics (concordance statistics) between two survival models using bootstrap resampling. Returns confidence intervals and a p-value for the difference in C-statistics. Useful for model evaluation and comparison.

Last updated

2.00 score 1 scripts 136 downloads

TwoDcDAPSA - Calculate TwoDcDAPSA: PROs-Joint Contrast (PJC) and Swollen–Tender Joints Contrast (STC) Scores and Quartiles

Provides a calculator for the two-dimensional clinical Disease Activity index for Psoriatic Arthritis (TwoDcDAPSA), a principal component-derived measure that complements the conventional clinical DAPSA score. TwoDcDAPSA captures residual variation in patient-reported outcomes (pain and patient global assessment) and joint counts (swollen and tender) after adjusting for standardized cDAPSA using natural spline coefficients derived from published models. Residuals are standardized and combined with fixed principal component loadings to yield two continuous component scores: the PROs-Joint Contrast (PJC) and the Swollen–Tender joints Contrast (STC), along with quartile-based groupings (including optional combined quartile groupings). The package applies pre-specified coefficients, residual standardization, and loadings to new datasets but does not estimate spline models or principal components itself.

Last updated

1.30 score 115 downloads

PJCcalculator - PROs-Joint Contrast (PJC) Calculator

Computes the Patient-Reported Outcomes (PROs) Joint Contrast (PJC), a residual-based summary that captures information left over after accounting for the clinical Disease Activity index for Psoriatic Arthritis (cDAPSA). PROs (pain and patient global assessment) and joint counts (swollen and tender) are standardized, then each component is adjusted for standardized cDAPSA using natural spline coefficients that were derived from previously published models. The resulting residuals are standardized and combined using fixed principal component loadings, to yield a continuous PJC score and quartile groupings. This package provides a calculator for applying those published coefficients to new datasets; it does not itself estimate spline models or principal components.

Last updated

1.00 score 171 downloads