Next Article in Journal
On the Sampling Size for Inverse Sampling
Previous Article in Journal
Selected Payback Statistical Contributions to Matrix/Linear Algebra: Some Counterflowing Conceptualizations
 
 
Article
Peer-Review Record

Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data

Stats 2022, 5(4), 1113-1129; https://doi.org/10.3390/stats5040066
by Sudaraka Tholkage, Qi Zheng and Karunarathna B. Kulasekera *
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Stats 2022, 5(4), 1113-1129; https://doi.org/10.3390/stats5040066
Submission received: 3 October 2022 / Revised: 20 October 2022 / Accepted: 21 October 2022 / Published: 10 November 2022
(This article belongs to the Section Survival Analysis)

Round 1

Reviewer 1 Report

  1. Introduce the numbered mathematics with consistency. Examples include “Equation (1)” on p4, while “(5)” and “4” on p5.

  2. In numerical studies, authors will need to include a case < n=100, to observe the behavior of the proposed method when the sample is small. Additionally, it would be good to include an application with a small sample, if possible.  

  3. For future research it is suggested to obtain the confidence intervals of the proposed estimators and its empirical coverage probability through simulation study.

Author Response

Please see attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

In this paper, the authors developed a generalized conditional KM estimator with desirable asymptotic properties for functional data and a bandwidth selection approach based on time-dependent Brier scores. A real data example is given for illustration of their results. Overall, the manuscript is well-written and an interesting study. It should be considered for publication in Stats.

Author Response

Please see attached.

Author Response File: Author Response.pdf

Back to TopTop