首先得了解一般线性回归，因为和mixed model 的内核是一样的，然后再看看mixed model 的原理，搞清楚对什么变量用fixed effect, 对什么上random effect。R包的话，比较常用lme4和glmer。
Fehrmann L, Lehtonen A, Kleinn C, Tomppo E (2008) Comparison of linear and mixed-effect regression models and a k-nearest neighbour approach for estimation of single-tree biomass. Can J For Res 38:1-9Comparison of linear and mixed-effect regression models and a k-nearest neighbour ...
Bayesian Analysis of Mixed-effect Regression Models Driven by Ordinary Differential EquationsBayesian inferenceB-splinesLongitudinal dataODE modelsRandom effectsTwo-step method.Non-linear regression models with regression functions specified by ordinary differential equations (ODEs) involving some unknown ...
These powerful models will allow you to explore data with a more complicated structure than a standard linear regression. The course then teaches generalized linear mixed-effect regressions. Generalized linear mixed-effects models allow you to model more kinds of data, including binary responses and ...
Note that you could also easily compute the credible interval around the regression line using the posterior draw from the model coefficient. Hopefully with all this material you should be able to apply linear mixed effect models to your data and to derive the usual information from these models...
Linear mixed-effect model LR: Logistic regression References Albrich K, Rammer W, Turner MG, Ratajczak Z, Braziunas KH, Hansen WD, Seidl R (2020) Simulating forest resilience: a review. Glob Ecol Biogeogr 29(12):2082–2096 Article Google Scholar Ashton MS, Kelty MJ (2018) The practic...
. All these factors are normalized and accordingly adjusted by using appropriate weights on the basis of their relative importance. The performance measures are obtained for each cricketer separately in all the four seasons of IPL played so far, and the regression model with random regression coe...
Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models Several tests for a zero random effect variance in linear mixed models are compared. This testing problem is non-regular because the tested parameter is on... F Scheipl,S ...
We also describe a boundary issue on testing for linearity of a regression function using the relationship between linear mixed effect models and penalized spline models. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Data Reduction, Smoothing, and Filtering ...
Whenever I try on some new machine learning or statistical package, I will fit a mixed effect model. It is better than linear regression (or MNIST for that matter, as it is just a large logistic regression) since linear regressions are almost too easy to fit. Hence this collection of code...