Maximum-likelihood estimation of beta regression models for responses derived from bounded rating scales. Observations are treated as interval-censored on (0, 1) after a scale-to-unit transformation,
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The betaregscale package is a library of R functions for fitting beta regression models to interval-censored transformed scale data, allowing for fixed or variable dispersion.
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取自儲存庫 README
正在載入完整 README。 以下為已儲存的摘錄。
Patient-reported outcome measures (PROMs) on bounded rating scales, such as the
Numerical Rating Scale (NRS-11, NRS-21, NRS-101), Visual Analogue Scale (VAS),
or Likert-type instruments, are ubiquitous in clinical research. Standard analyses
treat these bounded, discrete scores as exact continuous values via ordinary least
squares (OLS), silently violating two core assumptions: natural scale boundaries
are ignored, and the inherent heteroscedasticity of bounded responses is
misrepresented.檢視完整 README ↗目前無法載入完整 README。請透過原文連結閱讀。 以下為已儲存的摘錄。
Patient-reported outcome measures (PROMs) on bounded rating scales, such as the
Numerical Rating Scale (NRS-11, NRS-21, NRS-101), Visual Analogue Scale (VAS),
or Likert-type instruments, are ubiquitous in clinical research. Standard analyses
treat these bounded, discrete scores as exact continuous values via ordinary least
squares (OLS), silently violating two core assumptions: natural scale boundaries
are ignored, and the inherent heteroscedasticity of bounded responses is
misrepresented.檢視完整 README ↗