This project demonstrates the use of IBM SPSS Modeler 18.0 to create a linear regression model. The model predicts the target variable (dependent variable) based on one or more predictor variables ...

Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for unbalanced ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 66, No. 1 (2004), pp. 131-143 (13 pages) 'Delete = replace' is a powerful and intuitive modelling identity. This ...

GWAS was performed on serum uric acid levels using FastGWA and a mixed linear model. FastGWA applied linear regression with SNPs as predictors and age and sex as covariates, while the mixed model ...

Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose ...

Just as PROC GLM is the flagship procedure for fixed-effect linear models, the MIXED procedure is the flagship procedure for random- and mixed-effect linear models. PROC MIXED fits a variety of mixed ...