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Title: Compute Cortisol Sine Score (CSS) for Diurnal Cortisol Analysis
Version: 0.1.0
Description: Computes a single scalar metric for diurnal cortisol cycle analysis, the Cortisol Sine Score (CSS). The score is calculated as the sum over time points of concentration multiplied by sin(2 * pi * time / 24), giving positive weights to morning time points and negative weights to evening ones. The method is model-free, robust, and suitable for regression, classification, clustering, and biomarker research.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.2
Depends: R (≥ 4.1.0)
Imports: purrr, magrittr, dplyr
Suggests: tibble
URL: https://github.com/simone-anza/CortSineScore
BugReports: https://github.com/simone-anza/CortSineScore/issues
NeedsCompilation: no
Packaged: 2025-10-15 20:33:06 UTC; simon
Author: Simone Anzà [aut, cre]
Maintainer: Simone Anzà <simoneanza@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-20 19:40:14 UTC

Compute Cortisol Sine Score (CSS)

Description

Calculates the Cortisol Sine Score using timepoint-specific sine weights extracted from column names like "time_0200", "time_1400", etc.

Usage

compute_css(data, verbose = FALSE)

Arguments

data

A data.frame or tibble with subject ID in the first column and cortisol values in time_* columns. The time columns must be named using 24-hour format, e.g. time_0200, time_1400, etc.

verbose

Logical; if TRUE, returns the contribution of each timepoint to the CSS.

Value

A tibble with subject ID and cortisol_sin_score. If verbose = TRUE, includes individual contributions.

Examples

# Minimal, always-runnable example using base data.frame
df <- data.frame(
  subject_ID = c("S1", "S2"),
  time_0200 = c(2, 1),
  time_0600 = c(5, 2),
  time_1000 = c(4, 3),
  time_1400 = c(3, 2),
  time_1800 = c(1, 1),
  time_2200 = c(0.5, 0.3),
  stringsAsFactors = FALSE
)
compute_css(df)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.