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Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods

BMC Medical Research Methodology
We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis.
4 months ago

Federated statistical analysis: non-parametric testing and quantile estimation

Frontiers
In this work, we take a close look at the effects of federated analysis on two very basic problems, non-parametric comparison of two groups and quantile...
5 months ago

Simulation-based prior knowledge elicitation for parametric Bayesian models

Nature
A central characteristic of Bayesian statistics is the ability to consistently incorporate prior knowledge into various modeling processes.
4 months ago

Optimal subsampling for semi-parametric accelerated failure time models with massive survival data using a rank-based approach

Wiley Online Library
Subsampling is a practical strategy for analyzing vast survival data, which are progressively encountered across diverse research domains.
3 months ago

Effect Size Measures for Wilcoxon Signed-Rank Test in Likert Scale Data Analysis?

ResearchGate
Read 3 answers by scientists to the question asked by Adam R.S. Barton on Feb 24, 2024.
9 months ago

Cracking an interview in statistics for ML

Times of India
Data scientists perform descriptive statistical activities to get a firm hold on the data before training ML models.
1 month ago

Predicting overall survival from tumor dynamics metrics using parametric statistical and machine learning models: application to patients with RET-altered solid tumors

Frontiers
The proposed ML approach is able to adequately predict patient OS across RET-altered solid tumors, including non-small cell lung cancer, medullary thyroid...
5 months ago

NOTE: non-parametric oversampling technique for explainable credit scoring

Nature
Credit scoring models are critical for financial institutions to assess borrower risk and maintain profitability.
1 month ago

Nonparametric Statistics: Overview, Types, and Examples

Investopedia
Nonparametric statistics refer to a statistical method in which the data is not required to fit a normal distribution. Rankings should not change.
92 months ago

(PDF) THE POWER OF INFERENTIAL STATISTICAL TOOLS IN MAKING DECISION RULE IN RESEARCH

ResearchGate
PDF | This study examined the effectiveness of inferential statistical tools of analysis for strategic decision making in the public sector...
2 months ago