# 혼합효과

일반화 선형 혼합효과 모델

일반화 선형 혼합효과(GLME) 모델은 응답 변수를 모델링할 때 고정효과와 임의효과를 모두 포함합니다. 이 모델 유형은 군집화 변수의 임의효과를 포함하여 데이터 세트의 전역 추세와 국소 추세를 설명할 수 있습니다. GLME 모델은 응답 변수가 정규분포가 아닌 데이터에 대한 Linear Mixed-Effects Models(LME)의 일반화입니다. `fitglme`를 사용하여 `GeneralizedLinearMixedModel` 객체를 만듭니다.

## 클래스

 `GeneralizedLinearMixedModel` Generalized linear mixed-effects model class

## 함수

모두 확장

 `fitglme` Fit generalized linear mixed-effects model `refit` Refit generalized linear mixed-effects model
 `predict` Predict response of generalized linear mixed-effects model `random` Generate random responses from fitted generalized linear mixed-effects model `fitted` Fitted responses from generalized linear mixed-effects model `fixedEffects` Estimates of fixed effects and related statistics `randomEffects` Estimates of random effects and related statistics
 `anova` Analysis of variance for generalized linear mixed-effects model `coefCI` Confidence intervals for coefficients of generalized linear mixed-effects model `coefTest` Hypothesis test on fixed and random effects of generalized linear mixed-effects model `compare` Compare generalized linear mixed-effects models `covarianceParameters` Extract covariance parameters of generalized linear mixed-effects model `designMatrix` Fixed- and random-effects design matrices `partialDependence` Compute partial dependence (R2020b 이후) `residuals` Residuals of fitted generalized linear mixed-effects model `response` Response vector of generalized linear mixed-effects model
 `plotPartialDependence` Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots `plotResiduals` Plot residuals of generalized linear mixed-effects model

## 도움말 항목

• Fit a Generalized Linear Mixed-Effects Model

Fit a generalized linear mixed-effects model (GLME) to sample data.

• Generalized Linear Mixed-Effects Models

Generalized linear mixed-effects (GLME) models describe the relationship between a response variable and independent variables using coefficients that can vary with respect to one or more grouping variables, for data with a response variable distribution other than normal.

• Wilkinson Notation

Wilkinson notation provides a way to describe regression and repeated measures models without specifying coefficient values.