The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

A static portfolio offers passive, market-neutral exposure to convertible arbitrage. Find out why it's an efficient ...

Correlation Analysis: Computes correlation coefficients between different weather variables and electricity prices. Linear Regression Models: Fits regression models to examine the impact of weather ...

Design A cross-sectional study was conducted between April 2022 and December 2022. Pearson’s correlation coefficients and multiple linear regression analyses were employed to estimate the correlation ...

The correlation between variables was explored with multiple linear regression analyses, with the covariance of the model (R 2) and the standardised correlation coefficient presented. We performed all ...

This project performs a simple linear regression analysis using Python and Pandas. It calculates essential statistical metrics such as means, summations, correlation coefficient, and the linear ...

Linear regression analysis showed a significant association ... Interestingly, the percentage EDC-10 ES volume showed a higher correlation coefficient (R=0.55) than that for aneurysm volume (R=0.38).

Using a within-subject random effects regression analysis allows an estimate of overall ... a non-parametric approach was taken (Kendall τ rank correlation coefficient).8 To address research question ...

Using the 2 min Pilot study data, a multiple linear regression model was used to investigate ... The Pearson least mean squares correlation coefficient was then used to report the correlation between ...

The multiple linear regression analysis indicated lens wearing time (p=0.02) was found to be a statistically significant effect on the change of SER in the DISC group and the coefficient of covariates ...