Results 131 to 140 of about 15,601,125 (299)

Choosing informative priors in Bayesian regression models: a simulation study and tutorial using Stan and R

open access: yesFrontiers in Psychology
BackgroundBayesian regression models provide a robust framework for complex data analysis, which is particularly advantageous in scenarios with small sample sizes, common in psychology or medical research.
Daniel Lüdecke   +5 more
doaj   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

open access: yesMolecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq   +8 more
wiley   +1 more source

A pilot self-coach alignment audit in NCAA collegiate rowers: field feasibility, null findings, and design-sensitivity analysis for future self-verification research

open access: yesFrontiers in Sports and Active Living
BackgroundTesting relational mechanisms like self-verification (SV) in competitive collegiate sport is constrained by field-feasible measurement and the small-N problem.
Zacharias Papadakis   +2 more
doaj   +1 more source

Circulating microRNA signatures of cachexia and cancer in Canis familiaris as a comparative oncology model for human disease

open access: yesMolecular Oncology, EarlyView.
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park   +6 more
wiley   +1 more source

Comparison of Matrix Decomposition in Null Space-Based LDA Method

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Problems with small sample sizes and high dimensionality are common in pattern recognition. Almost all machine learning algorithms degrade in high-dimensional data, so that singularities in the scatter matrices, the main problem of the Linear ...
Carissa Devina Usman   +2 more
doaj   +1 more source

Oversampling and replacement strategies in propensity score matching: a critical review focused on small sample size in clinical settings. [PDF]

open access: yesBMC Med Res Methodol, 2021
Bottigliengo D   +10 more
europepmc   +1 more source

Preoperative circulating tumor cells integrated with imaging analysis for prognostic evaluation in head and neck squamous cell carcinoma

open access: yesMolecular Oncology, EarlyView.
Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach   +9 more
wiley   +1 more source

Bootstrapping long memory tests: some Monte Carlo results [PDF]

open access: yes
We investigate the bootstrapped size and power properties of five long memory tests, including the modified R/S, KPSS and GPH tests. In small samples, the moving block bootstrap controls the empirical size of the tests.
M Izzeldin, A Murphy
core  

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