Methodological Comparison of Mapping the Expanded Prostate Cancer Index Composite to EuroQoL-5D-3L Using Cross-Sectional and Longitudinal Data: Secondary Analysis of NRG/RTOG 0415 The ability to ...

Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a ...

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can use R-style formulas. First, you need to import statsmodels and its ...

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...

Choong Nyoung Kim and Raymond McLeod, Jr. Analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...