Centered Isotonic Regression: Point and Interval Estimation for Dose-Response Studies
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Abstract (arXiv)
Univariate isotonic regression (IR) has been used for nonparametric estimation in dose-response and dose-finding studies. One undesirable property of IR is the prevalence of piecewise-constant stretches in its estimates, whereas the dose-response function is usually assumed to be strictly increasing. We propose a simple modification to IR, called centered isotonic regression (CIR). CIR's estimates are strictly increasing in the interior of the dose range. In the absence of monotonicity violations, CIR and IR both return the original observations. Numerical examination indicates that for sample sizes typical of dose-response studies and with realistic dose-response curves, CIR provides a substantial reduction in estimation error compared with IR when monotonicity violations occur. We also develop analytical interval estimates for IR and CIR, with good coverage behavior. An R package implements these point and interval estimates.
Key facts. Cited by 5 papers in the map (data through 13 Oct 2026). First posted on arXiv 21 Jan 2017.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 2.
5 papers.
- 2024Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraphcited by 105
- 2025Rethinking Early Stopping: Refine, Then Calibratecited by 15
- 2023Stratification of uncertainties recalibrated by isotonic regression and its impact on calibration error statisticscited by 6
- 2026CalArena: A Large-Scale Post-Hoc Calibration Benchmarkcited by 1
- 2026Shared Doubt: Zero-Shot Cross-Lingual Confidence Estimation for Language Modelscited by 1
- 2026Shared Doubt: Zero-Shot Cross-Lingual Confidence Estimation for Language Models29 May 2026
- 2026CalArena: A Large-Scale Post-Hoc Calibration Benchmark28 May 2026
- 2025Rethinking Early Stopping: Refine, Then Calibrate31 Jan 2025
- 2024Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph21 Jun 2024
- 2023Stratification of uncertainties recalibrated by isotonic regression and its impact on calibration error statistics8 Jun 2023