Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference.
@article{Feng2021TestOS, title={Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference.}, author={Huijie Feng and Yang Ning and Jiwei Zhao}, journal={arXiv: Methodology}, year={2021} }
This work is motivated by learning the individualized minimal clinically important difference, a vital concept to assess clinical importance in various biomedical studies. We formulate the scientific question into a high-dimensional statistical problem where the parameter of interest lies in an individualized linear threshold. The goal of this paper is to develop a hypothesis testing procedure for the significance of a single element in this high-dimensional parameter as well as for the…
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SHOWING 1-10 OF 49 REFERENCES
TEST OF SIGNIFICANCE FOR HIGH-DIMENSIONAL LONGITUDINAL DATA.
- Mathematics, Computer ScienceAnnals of statistics
- 2020
A new quadratic decorrelated inference function approach is proposed, which simultaneously removes the impact of nuisance parameters and incorporates the correlation to enhance the efficiency of the estimation procedure.
The minimal clinically important difference raised the significance of outcome effects above the statistical level, with methodological implications for future studies.
- MedicineJournal of clinical epidemiology
- 2017
Confidence intervals and hypothesis testing for high-dimensional regression
- Mathematics, Computer ScienceJ. Mach. Learn. Res.
- 2014
This work considers here high-dimensional linear regression problem, and proposes an efficient algorithm for constructing confidence intervals and p-values, based on constructing a 'de-biased' version of regularized M-estimators.
Confidence intervals for low dimensional parameters in high dimensional linear models
- Mathematics, Computer Science
- 2011
The method proposed turns the regression data into an approximate Gaussian sequence of point estimators of individual regression coefficients, which can be used to select variables after proper thresholding, and demonstrates the accuracy of the coverage probability and other desirable properties of the confidence intervals proposed.
Foundations of the minimal clinically important difference for imaging.
- Computer ScienceThe Journal of rheumatology
- 2001
A generic conceptual framework for defining and validating the concept of minimal clinically important difference is developed, which is an experimentally driven approach, asking such questions as "What carries the least penalty?".
Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses
- Computer Science, MathematicsThe Annals of Statistics
- 2022
It is proved that the resulting estimator is minimax rate optimal up to a logarithmic factor, and the Lepski's method is developed to achieve the adaption to the unknown sparsity and smoothness of the conditional density of X given the response $Y$ and the covariates $Z.
Linking clinical relevance and statistical significance in evaluating intra-individual changes in health-related quality of life.
- Medicine, PsychologyMedical care
- 1999
The use of the SEM to evaluate individual patient change should be explored among other health-related quality of life instruments with established standards for clinically relevant differences.
Measurement of health status. Ascertaining the minimal clinically important difference.
- Medicine, PsychologyControlled clinical trials
- 1989
Double/Debiased Machine Learning for Treatment and Structural Parameters
- Computer Science
- 2017
This work revisits the classic semiparametric problem of inference on a low dimensional parameter θ_0 in the presence of high-dimensional nuisance parameters η_0 and proves that DML delivers point estimators that concentrate in a N^(-1/2)-neighborhood of the true parameter values and are approximately unbiased and normally distributed, which allows construction of valid confidence statements.
Minimal clinically important difference: defining what really matters to patients.
- MedicineJAMA
- 2014
Findings from a clinical trial evaluating whether acupuncture improved pain or overall functional outcomes compared with no acupuncture among patients with chronic knee pain are reported in this issue of JAMA.