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Stats, Volume 3, Issue 2

2020 June - 6 articles

Cover Story: Restricted mean survival time (RMST) is experiencing a renaissance and is advocated as a model-free, easy-to-interpret alternative to proportional hazard regression. Estimation of RMST and associated variance is mainly done by numerical integration of Kaplan–Meier curves. Pseudo-observations and the flexible parametric survival method are the two main alternatives to the Kaplan–Meier method. Flexible parametric survival methods outperform efficacy-wise both competitors, but the differences are small to negligible. RMST estimation and associated variance can be done with any of the three methods depending on the needs and aims of the researchers. The Kaplan–Meier method is the easiest to implement, flexible parametric survival models are the most powerful, while pseudo-observations allow for adjustment for relevant co-variates. View this paper.
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Articles (6)

  • Article
  • Open Access
25 Citations
4,728 Views
21 Pages

Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks

  • Paulo Canas Rodrigues,
  • Olushina Olawale Awe,
  • Jonatha Sousa Pimentel and
  • Rahim Mahmoudvand

1 June 2020

A proper understanding and analysis of suitable models involved in forecasting currency exchange rates dynamics is essential to provide reliable information about the economy. This paper deals with model fit and model forecasting of eight time series...

  • Article
  • Open Access
3 Citations
2,893 Views
17 Pages

29 May 2020

This paper aims to solve the problem of fitting a nonparametric regression function with right-censored data. In general, issues of censorship in the response variable are solved by synthetic data transformation based on the Kaplan–Meier estima...

  • Article
  • Open Access
15 Citations
9,791 Views
13 Pages

26 May 2020

Restricted Mean Survival Time ( R M S T ) experiences a renaissance and is advocated as a model-free, easy to interpret alternative to proportional hazards regression and hazard rates with implication in causal inference. Estimation of R M ...

  • Article
  • Open Access
10 Citations
10,425 Views
10 Pages

The Prediction of Batting Averages in Major League Baseball

  • Sarah R. Bailey,
  • Jason Loeppky and
  • Tim B. Swartz

3 April 2020

The prediction of yearly batting averages in Major League Baseball is a notoriously difficult problem where standard errors using the well-known PECOTA (Player Empirical Comparison and Optimization Test Algorithm) system are roughly 20 points. This p...

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Stats - ISSN 2571-905X