调用mF@X应返回固定效果设计矩阵（glmm中边缘和条件R ^ 2必需）。
但它不起作用。
在模型结构中是否列出了这样的矩阵？
我感谢任何建议。
str(mF)
Formal class 'glmerMod' [package "lme4"] with 13 slots
..@ resp :Reference class 'glmResp' [package "lme4"] with 11 fields
.. ..$ Ptr :<externalptr>
.. ..$ mu : num [1:480] 0.168 0.356 0.168 0.356 0.284 ...
.. ..$ offset : num [1:480] 0 0 0 0 0 0 0 0 0 0 ...
.. ..$ sqrtXwt: num [1:480] 0.373 0.479 0.373 0.479 0.451 ...
.. ..$ sqrtrwt: num [1:480] 2.68 2.09 2.68 2.09 2.22 ...
.. ..$ weights: num [1:480] 1 1 1 1 1 1 1 1 1 1 ...
.. ..$ wtres : num [1:480] -0.449 -0.744 -0.449 1.344 -0.629 ...
.. ..$ y : num [1:480] 0 0 0 1 0 0 0 1 0 0 ...
.. ..$ eta : num [1:480] -1.603 -0.591 -1.603 -0.591 -0.927 ...
.. ..$ family :List of 11
.. .. ..$ family : chr "binomial"
.. .. ..$ link : chr "logit"
.. .. ..$ linkfun :function (mu)
.. .. ..$ linkinv :function (eta)
.. .. ..$ variance :function (mu)
.. .. ..$ dev.resids:function (y, mu, wt)
.. .. ..$ aic :function (y, n, mu, wt, dev)
.. .. ..$ mu.eta :function (eta)
.. .. ..$ validmu :function (mu)
.. .. ..$ valideta :function (eta)
.. .. ..$ simulate :function (object, nsim)
.. .. ..- attr(*, "class")= chr "family"
.. ..$ n : num [1:480] 1 1 1 1 1 1 1 1 1 1 ...
.. ..and 41 methods, of which 29 are possibly relevant:
.. .. aic, allInfo, allInfo#lmResp, copy#envRefClass, devResid, fam,
.. .. initialize, initialize#lmResp, initializePtr, Laplace, link, muEta, ptr,
.. .. ptr#lmResp, resDev, setOffset, setResp, setTheta, setWeights, sqrtWrkWt,
.. .. theta, updateMu, updateMu#lmResp, updateWts, variance, wrkResids,
.. .. wrkResp, wrss, wtWrkResp
..@ Gp : int [1:3] 0 60 72
..@ call : language lme4::glmer(formula = Colour ~ Treatment + Habitat + (1 | Population) + (1 | Container), data = Data, family = "binomial", control = structure(list( ...
..@ frame :'data.frame': 480 obs. of 5 variables:
.. ..$ Colour : int [1:480] 0 0 0 1 0 0 0 1 0 0 ...
.. ..$ Treatment : Factor w/ 2 levels "Cont","Exp": 1 2 1 2 1 2 1 2 1 2 ...
.. ..$ Habitat : Factor w/ 2 levels "A","B": 1 1 1 1 2 2 2 2 1 1 ...
.. ..$ Population: int [1:480] 1 1 1 1 1 1 1 1 1 1 ...
.. ..$ Container : int [1:480] 2 2 2 2 2 2 2 2 4 4 ...
.. ..- attr(*, "terms")=Classes 'terms', 'formula' length 3 Colour ~ Treatment + Habitat + (1 + Population) + (1 + Container)
.. .. .. ..- attr(*, "variables")= language list(Colour, Treatment, Habitat, Population, Container)
.. .. .. ..- attr(*, "factors")= int [1:5, 1:4] 0 1 0 0 0 0 0 1 0 0 ...
.. .. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. .. ..$ : chr [1:5] "Colour" "Treatment" "Habitat" "Population" ...
.. .. .. .. .. ..$ : chr [1:4] "Treatment" "Habitat" "Population" "Container"
.. .. .. ..- attr(*, "term.labels")= chr [1:4] "Treatment" "Habitat" "Population" "Container"
.. .. .. ..- attr(*, "order")= int [1:4] 1 1 1 1
.. .. .. ..- attr(*, "intercept")= int 1
.. .. .. ..- attr(*, "response")= int 1
.. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
.. .. .. ..- attr(*, "predvars")= language list(Colour, Treatment, Habitat, Population, Container)
.. .. .. ..- attr(*, "dataClasses")= Named chr [1:5] "numeric" "factor" "factor" "numeric" ...
.. .. .. .. ..- attr(*, "names")= chr [1:5] "Colour" "Treatment" "Habitat" "Population" ...
.. .. .. ..- attr(*, "predvars.fixed")= language list(Colour, Treatment, Habitat)
.. ..- attr(*, "formula")=Class 'formula' length 3 Colour ~ Treatment + Habitat + (1 | Population) + (1 | Container)
.. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
..@ flist :List of 2
.. ..$ Container : Factor w/ 60 levels "2","4","6","8",..: 1 1 1 1 1 1 1 1 2 2 ...
.. ..$ Population: Factor w/ 12 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
.. ..- attr(*, "assign")= int [1:2] 1 2
..@ cnms :List of 2
.. ..$ Container : chr "(Intercept)"
.. ..$ Population: chr "(Intercept)"
..@ lower : num [1:2] 0 0
..@ theta : num [1:2] 0.0761 1.0537
..@ beta : num [1:3] -1.251 1.012 0.676
..@ u : num [1:72] -0.05 0.0254 -0.05 0.1008 -0.05 ...
..@ devcomp:List of 2
.. ..$ cmp : Named num [1:11] 27.3 8.5 438.1 10.6 448.7 ...
.. .. ..- attr(*, "names")= chr [1:11] "ldL2" "ldRX2" "wrss" "ussq" ...
.. ..$ dims: Named int [1:14] 480 480 3 477 2 72 1 1 0 2 ...
.. .. ..- attr(*, "names")= chr [1:14] "N" "n" "p" "nmp" ...
..@ pp :Reference class 'merPredD' [package "lme4"] with 18 fields
.. ..$ Lambdat:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:72] 0 1 2 3 4 5 6 7 8 9 ...
.. .. .. ..@ p : int [1:73] 0 1 2 3 4 5 6 7 8 9 ...
.. .. .. ..@ Dim : int [1:2] 72 72
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : NULL
.. .. .. .. ..$ : NULL
.. .. .. ..@ x : num [1:72] 0.0761 0.0761 0.0761 0.0761 0.0761 ...
.. .. .. ..@ factors : list()
.. ..$ LamtUt :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:960] 0 60 0 60 0 60 0 60 0 60 ...
.. .. .. ..@ p : int [1:481] 0 2 4 6 8 10 12 14 16 18 ...
.. .. .. ..@ Dim : int [1:2] 72 480
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : NULL
.. .. .. .. ..$ : NULL
.. .. .. ..@ x : num [1:960] 0.0284 0.3935 0.0365 0.5046 0.0284 ...
.. .. .. ..@ factors : list()
.. ..$ Lind : int [1:72] 1 1 1 1 1 1 1 1 1 1 ...
.. ..$ Ptr :<externalptr>
.. ..$ RZX : num [1:72, 1:3] 0.124 0.125 0.124 0.125 0.124 ...
.. ..$ Ut :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:960] 0 60 0 60 0 60 0 60 0 60 ...
.. .. .. ..@ p : int [1:481] 0 2 4 6 8 10 12 14 16 18 ...
.. .. .. ..@ Dim : int [1:2] 72 480
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:72] "2" "4" "6" "8" ...
.. .. .. .. ..$ : NULL
.. .. .. ..@ x : num [1:960] 0.373 0.373 0.479 0.479 0.373 ...
.. .. .. ..@ factors : list()
.. ..$ Utr : num [1:72] -0.094 -0.018 -0.094 0.058 -0.094 ...
.. ..$ V : num [1:480, 1:3] 0.373 0.479 0.373 0.479 0.451 ...
.. ..$ VtV : num [1:3, 1:3] 92.7 0 0 48.3 48.3 ...
.. ..$ Vtr : num [1:3] 15.738 0.879 3.455
.. ..$ X : num [1:480, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:480] "1" "2" "3" "4" ...
.. .. .. ..$ : chr [1:3] "(Intercept)" "TreatmentExp" "HabitatB"
.. .. ..- attr(*, "assign")= int [1:3] 0 1 2
.. .. ..- attr(*, "contrasts")=List of 2
.. .. .. ..$ Treatment: chr "contr.treatment"
.. .. .. ..$ Habitat : chr "contr.treatment"
.. ..$ Xwts : num [1:480] 0.373 0.479 0.373 0.479 0.451 ...
.. ..$ Zt :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:960] 0 60 0 60 0 60 0 60 0 60 ...
.. .. .. ..@ p : int [1:481] 0 2 4 6 8 10 12 14 16 18 ...
.. .. .. ..@ Dim : int [1:2] 72 480
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:72] "2" "4" "6" "8" ...
.. .. .. .. ..$ : NULL
.. .. .. ..@ x : num [1:960] 1 1 1 1 1 1 1 1 1 1 ...
.. .. .. ..@ factors : list()
.. ..$ beta0 : num [1:3] 0 0 0
.. ..$ delb : num [1:3] 0 0 0
.. ..$ delu : num [1:72] -0.05 0.0254 -0.05 0.1008 -0.05 ...
.. ..$ theta : num [1:2] 0.0761 1.0537
.. ..$ u0 : num [1:72] 0 0 0 0 0 0 0 0 0 0 ...
.. ..and 42 methods, of which 30 are possibly relevant:
.. .. b, beta, CcNumer, copy#envRefClass, initialize, initializePtr,
.. .. installPars, L, ldL2, ldRX2, linPred, P, ptr, RX, RXdiag, RXi, setBeta0,
.. .. setDelb, setDelu, setTheta, solve, solveU, sqrL, u, unsc, updateDecomp,
.. .. updateL, updateLamtUt, updateRes, updateXwts
..@ optinfo:List of 7
.. ..$ optimizer: chr "Nelder_Mead"
.. ..$ control :List of 3
.. .. ..$ xst : num [1:5] 0.02 0.02 0.0721 0.0421 0.0418
.. .. ..$ xt : num [1:5] 1.00e-05 1.00e-05 3.60e-05 2.11e-05 2.09e-05
.. .. ..$ verbose: int 0
.. ..$ derivs :List of 2
.. .. ..$ gradient: num [1:5] 4.64e-05 9.60e-05 -6.73e-05 -6.46e-05 -1.26e-04
.. .. ..$ Hessian : num [1:5, 1:5] 2.644 -0.247 0.162 -1.023 -0.625 ...
.. ..$ conv :List of 2
.. .. ..$ opt : num 0
.. .. ..$ lme4: list()
.. ..$ feval : num 232
.. ..$ warnings : list()
.. ..$ val : num [1:5] 0.0761 1.0537 -1.2511 1.0118 0.676
答案 0 :(得分：5)
您可以使用函数model.matrix来获取固定效果设计矩阵：
model.matrix(fit)
其中fit是glmer返回的对象。