The international journal of biostatistics
Jul 29, 2024
A two-group comparison test is generally performed on RNA sequencing data to detect differentially expressed genes (DEGs). However, the accuracy of this method is low due to the small sample size. To address this, we propose a method using fuzzy clus...
The international journal of biostatistics
Jun 14, 2023
There is widespread interest in using deep learning to build prediction models for medical imaging data. These deep learning methods capture the local structure of the image and require no manual feature extraction. Despite the importance of modeling...
The international journal of biostatistics
Aug 9, 2022
In finding effects of a binary treatment, practitioners use mostly either propensity score matching (PSM) or inverse probability weighting (IPW). However, many new treatment effect estimators are available now using propensity score and "prognostic s...
The international journal of biostatistics
Mar 25, 2022
The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past two decades. The problems of modeling, estimation and inference have been treated using...
The international journal of biostatistics
Aug 13, 2020
We propose a method for summarizing the strength of association between a set of variables and a multivariate outcome. Classical summary measures are appropriate when linear relationships exist between covariates and outcomes, while our approach prov...
The international journal of biostatistics
Dec 5, 2019
We present new methods for cell line classification using multivariate time series bioimpedance data obtained from electric cell-substrate impedance sensing (ECIS) technology. The ECIS technology, which monitors the attachment and spreading of mammal...
The international journal of biostatistics
Apr 16, 2019
We consider causal inference in observational studies with choice-based sampling, in which subject enrollment is stratified on treatment choice. Choice-based sampling has been considered mainly in the econometrics literature, but it can be useful for...
The international journal of biostatistics
Jun 8, 2018
UNLABELLED: In health and social sciences, research questions often involve systematic assessment of the modification of treatment causal effect by patient characteristics. In longitudinal settings, time-varying or post-intervention effect modifiers ...
The international journal of biostatistics
May 1, 2016
Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is ...
The international journal of biostatistics
May 1, 2016
OBJECTIVE: Consistent estimation of causal effects with inverse probability weighting estimators is known to rely on consistent estimation of propensity scores. To alleviate the bias expected from incorrect model specification for these nuisance para...