# NONPARAMETRIC STATISTICAL TESTS FOR CENSORED DATA

> **NIH NIH R01** · DANA-FARBER CANCER INST · 1991 · $173,145

## Abstract

During the next funding period of this grant, we will examine some
important questions in regression models for right-censored data.  The
issues we have chosen extend work conducted during the current project
period, and epidemiologic studies in cancer research.  More specifically,
we will investigate the following topics:

1.  A study of properties of methods for fitting nonlinear models for
covariate effects in proportional hazards regression.  In particular, we
will examine the loss of efficiency when overfitting nonlinear models, and
the effect on inference of adaptive knot placement of regression splines.


2.  Methods for inference in proportional hazards or relative risk
regression models when either outcome variables or covariates are either
measured with error, or are replaced by surrogate variables that are easier
to measure.

3.  Methods for parsimonious modeling of the association of survival data
and covariates when different covariate values do not produce proportional
conditional hazard functions.

4.  A study of significance tests that are sensitive to a wide range of
relationships between survival data and smooth (i.e. continuous)
covariates.

## Key facts

- **NIH application ID:** 3179297
- **Project number:** 2R01CA039929-07
- **Recipient organization:** DANA-FARBER CANCER INST
- **SAM.gov UEI:** DPMGH9MG1X67
- **Principal Investigator:** DAVID P HARRINGTON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 1991
- **Award amount:** $173,145
- **Award type:** 2
- **Project period:** 1984-09-01 → 1993-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/3179297

## Citation

> US National Institutes of Health, RePORTER application 3179297, NONPARAMETRIC STATISTICAL TESTS FOR CENSORED DATA (2R01CA039929-07). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/3179297. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*