2014-11-03 40 views
0

我試圖預測從我的混合效應模型(邏輯迴歸)的固定效應。我的模型是:試圖預測與lmer模型

MOD.MIX.1 <- glmer(PATCH_TYPE~PC1+PC2+PC3+JUL.DAY+(1|Study_area)+ 
        (1|ID),family=binomial,data=FOR.MODEL) 

我試圖預測模型是這樣的:

newdata <- with(MOD.MIX.1, expand.grid(PC1=unique(PC1), 
            PC2=mean(FOR.MODEL$PC2), 
            PC3=mean(FOR.MODEL$PC3), 
            JUL.DAY=mean(FOR.MODEL$JUL.DAY))) 

PREDICTPC1<-predict(MOD.MIX.1, newdata) 

這是錯誤我得到:

Error: couldn't evaluate grouping factor Study_area within model frame: 
     try adding grouping factor to data frame explicitly if possible 

這是什麼意思哪有我繼續?

數據:

structure(list(Study_area = structure(c(1L, 1L, 1L, 1L), .Label = c("GLQ", 
"MEN", "STB", "STN", "STO"), class = "factor"), PATCH_CODE = structure(c(2L, 
2L, 2L, 91L), .Label = c("A", "A1", "A2", "A3", "A4", "A5", "A6", 
"A7", "A8", "A9", "AA1", "AA2", "AA3", "AB1", "AB2", "AB3", "AC1", 
"AC2", "AC3", "AD1", "AD2", "AD3", "AE1", "AE2", "AF1", "AF2", 
"AG1", "AG2", "AG3", "AH1", "AH2", "AH3", "AI1", "AI2", "AI3", 
"AJ1", "AJ2", "AK1", "AK2", "AK3", "AL1", "AL2", "AL3", "AM1", 
"AM2", "AM3", "AN1", "AN2", "AO1", "AO2", "AO3", "AP1", "AP2", 
"AP3", "AP4", "AQ1", "AQ2", "AQ3", "AR1", "AR2", "AR3", "AS1", 
"AS2", "AS3", "AS4", "AT1", "AT2", "AT3", "AT4", "AU1", "AU2", 
"AU3", "AU4", "AV1", "AV2", "AV3", "AV4", "AW1", "AW2", "AW3", 
"AX1", "AX2", "AX3", "AY1", "AY2", "AY3", "AZ1", "AZ2", "AZ3", 
"B", "B1", "B2", "B3", "B4", "BA1", "BA2", "BA3", "BB", "BB1", 
"BB2", "BB3", "BC1", "BC2", "BC3", "BD1", "BD2", "BD3", "BE1", 
"BE2", "BE3", "BF1", "BF2", "BF3", "BG1", "BG2", "BG3", "BH1", 
"BH2", "BH3", "BI1", "BI2", "BI3", "BJ1", "BJ2", "BJ3", "BK1", 
"BK2", "BK3", "BL1", "BL2", "BL3", "BM1", "BM2", "BN1", "BN2", 
"BN3", "BO1", "BO2", "BO3", "BO4", "BP1", "BP2", "BP3", "BQ1", 
"BQ2", "BQ3", "BR1", "BR2", "BR3", "BS1", "BS2", "BT1", "BT2", 
"BT3", "BU1", "BU2", "BU3", "BV1", "BV2", "BV3", "BW1", "BX1", 
"BX2", "BY1", "BY2", "BY3", "BZ1", "BZ2", "BZ3", "BZ4", "C", 
"C1", "C2", "C3", "C4", "C5", "C6", "CA1", "CA2", "CA3", "CB1", 
"CB2", "CC", "CC1", "CC2", "CD1", "CE1", "CE2", "CF1", "CF2", 
"CG1", "CG2", "CH1", "CH2", "CI1", "CI2", "CJ1", "CJ2", "CK1", 
"CK2", "CL1", "CL2", "CM1", "CM2", "CN1", "CN2", "CO1", "CO2", 
"CO3", "D", "D1", "D2", "D3", "D4", "D5", "D6", "E", "E1", "E2", 
"E3", "E4", "F1", "F2", "F3", "F4", "F5", "G1", "G2", "G3", "G4", 
"G5", "G6", "G7", "G8", "H1", "H2", "H3", "H4", "HH", "I1", "I2", 
"I3", "I4", "J1", "J2", "J3", "J4", "J5", "J6", "J7", "J8", "J9", 
"K1", "K2", "K3", "K4", "K5", "L1", "L2", "L3", "M1", "M2", "M3", 
"M4", "M5", "M6", "N1", "N2", "N3", "O1", "O2", "O3", "O4", "O5", 
"O6", "P1", "P2", "P3", "P4", "Q1", "Q2", "Q3", "Q4", "Q5", "R1", 
"R2", "R3", "S1", "S2", "S3", "S4", "S5", "S6", "T1", "T2", "T3", 
"T4", "U1", "U2", "U3", "U4", "U5", "U6", "V1", "V2", "V3", "W1", 
"W2", "W3", "X1", "X2", "X3", "Y1", "Y2", "Y3", "Y4", "Z1", "Z2", 
"Z3"), class = "factor"), PATCH_NAME = structure(c(1L, 1L, 1L, 
35L), .Label = c("A", "AA", "AA ", "AB", "AB ", "AC", "AC ", 
"AD", "AD ", "AE", "AE ", "AF", "AF ", "AG", "AG ", "AH", "AI", 
"AJ", "AK", "AL", "AM", "AN", "AO", "AP", "AQ", "AR", "AS", "AT", 
"AU", "AV", "AW", "AX", "AY", "AZ", "B", "BA", "BB", "BC", "BD", 
"BE", "BF", "BG", "BH", "BI", "BJ", "BK", "BL", "BM", "BN", "BO", 
"BP", "BQ", "BR", "BS", "BT", "BU", "BV", "BW", "BX", "BY", "BZ", 
"C", "CA", "CB", "CC", "CD", "CE", "CF", "CG", "CH", "CI", "CJ", 
"CK", "CL", "CM", "CN", "CO", "D", "E", "F", "F ", "G", "G ", 
"H", "H ", "I", "I ", "J", "J ", "K", "K ", "L", "L ", "M", "M ", 
"N", "N ", "O", "O ", "P", "P ", "Q", "Q ", "R", "R ", "S", "S ", 
"T", "T ", "U ", "V", "V ", "W", "W ", "X", "X ", "Y", "Y ", 
"Z", "Z "), class = "factor"), REPLICATE = structure(c(1L, 1L, 
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8", "9", 
"B", "C", "H"), class = "factor"), REP_MES = c(19L, 19L, 19L, 
133L), Observer = structure(c(4L, 4L, 4L, 4L), .Label = c("CM", 
"JA", "JB", "JC", "SH", "SP", "TP"), class = "factor"), HAB_TYPE = structure(c(2L, 
2L, 2L, 2L), .Label = c("Grazed", "Ungrazed"), class = "factor"), 
    PATCH_TYPE = c(1, 0, 0, 1), Male_visits__all_ = c(3L, 0L, 
    0L, 1L), Male_visits__successful_ = c(3L, 0L, 0L, 1L), Male_visits__for_young_ = c(0L, 
    0L, 0L, 0L), Female_visits__all_ = c(1L, 0L, 0L, 0L), Female_visits__successful_ = c(1L, 
    0L, 0L, 0L), Female_visits__for_young_ = c(0L, 0L, 0L, 0L 
    ), Juv__Visits__all_ = c(0L, 0L, 0L, 0L), Juv__Visits__succ__ = c(0L, 
    0L, 0L, 0L), HERB_0 = c(0L, 0L, 40L, 10L), HERB_20 = c(0L, 
    0L, 10L, 0L), HERB_50 = c(0L, 0L, 0L, 0L), GRASS_0 = c(10L, 
    100L, 60L, 30L), GRASS_20 = c(0L, 20L, 0L, 0L), GRASS_50 = c(0L, 
    0L, 0L, 0L), RUSH_0 = c(0L, 0L, 0L, 0L), RUSH_20 = c(0L, 
    0L, 0L, 0L), RUSH_50 = c(0L, 0L, 0L, 0L), ERIC_0 = c(0L, 
    0L, 0L, 0L), ERIC_20 = c(0L, 0L, 0L, 0L), ERIC_50 = c(0L, 
    0L, 0L, 0L), BRACK_0 = c(0L, 0L, 0L, 0L), BRACK_20 = c(0L, 
    0L, 0L, 0L), BRACK_50 = c(0L, 0L, 0L, 0L), MOSS = c(0L, 0L, 
    0L, 0L), BARE = c(90L, 0L, 0L, 0L), WATER = c(0L, 0L, 0L, 
    0L), O_HUNG = structure(c(3L, 3L, 3L, 3L), .Label = c("BRA", 
    "GOR", "N", "RUS", "S"), class = "factor"), DISCREET = structure(c(5L, 
    17L, 17L, 5L), .Label = c("1", "10", "15", "1.5", "2", "20", 
    "25", "3", "4", "40", "5", "50", "6", "7", "8", "9", "NO" 
    ), class = "factor"), Notes = structure(c(21L, NA, NA, 21L 
    ), .Label = c("By burn", "Clear-felled conifer", "Concrete reservoir overflow", 
    "Female feeding 4 rf juvs, male sing", "Foraging figure includes flycatchin", 
    "Gorse", "Grassy area surrounded by juniper", "Male, female and 4 juvs, male singi", 
    "Male singing most of time, female f", "Patch of rushes", 
    "pr around nest (female removing fae", "Pr foraging, didn't appear to be pr", 
    "Pr provisioning at least 2 fledged", "Pr with 4 rf juvs", 
    "Pr with at least 1 rf young, male s", "Road", "Road edge", 
    "rows added as James Bray said the reference patches were the same in extensive bracken", 
    "Shorter grass under tree", "Shorter veg. surrounded by taller", 
    "Track", "Willow"), class = "factor"), Site = structure(c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_), .Label = c("A", "B", 
    "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", 
    "O", "P", "Q", "R", "S", "T"), class = "factor"), Site_visit = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_), DAY = c(17L, 17L, 
    17L, 17L), DEAD = c(0L, 0L, 0L, 0L), StartHour = c(6L, NA, 
    NA, 6L), StartMinute = c(0L, NA, NA, 0L), EndHour = c(6L, 
    NA, NA, 6L), EndMinute = c(30L, NA, NA, 30L), DURATION = c(30L, 
    NA, NA, 30L), EASTING = c(297736L, NA, NA, 297991L), NORTHING = c(703033L, 
    NA, NA, 702934L), ELEV = c(NA_integer_, NA_integer_, NA_integer_, 
    NA_integer_), MONTH = c(6L, 6L, 6L, 6L), ORIENTATION = structure(c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_), .Label = c("C", "N", 
    "S"), class = "factor"), PERCH = structure(c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_), .Label = c("B", "F", 
    "G", "R", "T"), class = "factor"), TERR = structure(c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_), .Label = "M", class = "factor"), 
    VISIT_NO = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_ 
    ), JUL.DAY = c(17, 17, 17, 17), ID = c("GLQ_JC_19", "GLQ_JC_19", 
    "GLQ_JC_19", "GLQ_JC_133"), PC1 = c(0.0435645668204425, 0.72948034145072, 
    0.803061560901585, 0.259840578885553), PC2 = c(-0.593400745369881, 
    0.848541838597916, -1.19902967772894, -0.58625628136995), 
    PC3 = c(-0.729043630624223, -0.534297045616433, 0.655933470491286, 
    -0.518820312795394)), .Names = c("Study_area", "PATCH_CODE", 
"PATCH_NAME", "REPLICATE", "REP_MES", "Observer", "HAB_TYPE", 
"PATCH_TYPE", "Male_visits__all_", "Male_visits__successful_", 
"Male_visits__for_young_", "Female_visits__all_", "Female_visits__successful_", 
"Female_visits__for_young_", "Juv__Visits__all_", "Juv__Visits__succ__", 
"HERB_0", "HERB_20", "HERB_50", "GRASS_0", "GRASS_20", "GRASS_50", 
"RUSH_0", "RUSH_20", "RUSH_50", "ERIC_0", "ERIC_20", "ERIC_50", 
"BRACK_0", "BRACK_20", "BRACK_50", "MOSS", "BARE", "WATER", "O_HUNG", 
"DISCREET", "Notes", "Site", "Site_visit", "DAY", "DEAD", "StartHour", 
"StartMinute", "EndHour", "EndMinute", "DURATION", "EASTING", 
"NORTHING", "ELEV", "MONTH", "ORIENTATION", "PERCH", "TERR", 
"VISIT_NO", "JUL.DAY", "ID", "PC1", "PC2", "PC3"), row.names = c(NA, 
4L), class = "data.frame") 

模型結構

str(MOD.MIX.1) 
Formal class 'glmerMod' [package "lme4"] with 13 slots 
    [email protected] resp :Reference class 'glmResp' [package "lme4"] with 11 fields 
    .. ..$ Ptr :<externalptr> 
    .. ..$ mu  : num [1:1208] 0.316 0.341 0.31 0.325 0.222 ... 
    .. ..$ offset : num [1:1208] -0.42 -0.308 -0.45 -0.38 -0.903 ... 
    .. ..$ sqrtXwt: num [1:1208] 0.465 0.474 0.462 0.468 0.416 ... 
    .. ..$ sqrtrwt: num [1:1208] 2.15 2.11 2.16 2.14 2.41 ... 
    .. ..$ weights: num [1:1208] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ wtres : num [1:1208] 1.47 -0.719 -0.67 1.441 -0.534 ... 
    .. ..$ y  : num [1:1208] 1 0 0 1 0 0 1 0 0 1 ... 
    .. ..$ eta : num [1:1208] -0.771 -0.659 -0.801 -0.731 -1.254 ... 
    .. ..$ 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 [1:1208] 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 
    [email protected] Gp  : int [1:3] 0 220 222 
    [email protected] call : language glmer(formula = PATCH_TYPE ~ PC1 + PC2 + PC3 + JUL.DAY + (1 | Study_area) +  (1 | ID), data = FOR.MODEL, family = binomial) 
    [email protected] frame :'data.frame': 1208 obs. of 7 variables: 
    .. ..$ PATCH_TYPE: num [1:1208] 1 0 0 1 0 0 1 0 0 1 ... 
    .. ..$ PC1  : num [1:1208] 0.0436 0.7295 0.8031 0.2598 1.1722 ... 
    .. ..$ PC2  : num [1:1208] -0.593 0.849 -1.199 -0.586 -1.66 ... 
    .. ..$ PC3  : num [1:1208] -0.729 -0.534 0.656 -0.519 2.483 ... 
    .. ..$ JUL.DAY : num [1:1208] 17 17 17 17 17 17 17 17 17 20 ... 
    .. ..$ Study_area: Factor w/ 2 levels "GLQ","MEN": 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ ID  : chr [1:1208] "GLQ_JC_19" "GLQ_JC_19" "GLQ_JC_19" "GLQ_JC_133" ... 
    .. ..- attr(*, "terms")=Classes 'terms', 'formula' length 3 PATCH_TYPE ~ PC1 + PC2 + PC3 + JUL.DAY + (1 + Study_area) + (1 + ID) 
    .. .. .. ..- attr(*, "variables")= language list(PATCH_TYPE, PC1, PC2, PC3, JUL.DAY, Study_area, ID) 
    .. .. .. ..- attr(*, "factors")= int [1:7, 1:6] 0 1 0 0 0 0 0 0 0 1 ... 
    .. .. .. .. ..- attr(*, "dimnames")=List of 2 
    .. .. .. .. .. ..$ : chr [1:7] "PATCH_TYPE" "PC1" "PC2" "PC3" ... 
    .. .. .. .. .. ..$ : chr [1:6] "PC1" "PC2" "PC3" "JUL.DAY" ... 
    .. .. .. ..- attr(*, "term.labels")= chr [1:6] "PC1" "PC2" "PC3" "JUL.DAY" ... 
    .. .. .. ..- attr(*, "order")= int [1:6] 1 1 1 1 1 1 
    .. .. .. ..- attr(*, "intercept")= int 1 
    .. .. .. ..- attr(*, "response")= int 1 
    .. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
    .. .. .. ..- attr(*, "predvars")= language list(PATCH_TYPE, PC1, PC2, PC3, JUL.DAY, Study_area, ID) 
    .. .. .. ..- attr(*, "dataClasses")= Named chr [1:7] "numeric" "numeric" "numeric" "numeric" ... 
    .. .. .. .. ..- attr(*, "names")= chr [1:7] "PATCH_TYPE" "PC1" "PC2" "PC3" ... 
    .. .. .. ..- attr(*, "predvars.fixed")= language list(PATCH_TYPE, PC1, PC2, PC3, JUL.DAY) 
    .. ..- attr(*, "formula")=Class 'formula' length 3 PATCH_TYPE ~ PC1 + PC2 + PC3 + JUL.DAY + (1 | Study_area) + (1 | ID) 
    .. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
    [email protected] flist :List of 2 
    .. ..$ ID  : Factor w/ 220 levels "GLQ_JB_58","GLQ_JB_59",..: 19 19 19 4 4 4 5 5 5 6 ... 
    .. ..$ Study_area: Factor w/ 2 levels "GLQ","MEN": 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..- attr(*, "assign")= int [1:2] 1 2 
    [email protected] cnms :List of 2 
    .. ..$ ID  : chr "(Intercept)" 
    .. ..$ Study_area: chr "(Intercept)" 
    [email protected] lower : num [1:2] 0 0 
    [email protected] theta : num [1:2] 0 0.365 
    [email protected] beta : num [1:5] -0.88409 0.57692 -0.14263 -0.40055 0.00369 
    [email protected] u  : num [1:222] 0 0 0 0 0 0 0 0 0 0 ... 
    [email protected] devcomp:List of 2 
    .. ..$ cmp : Named num [1:11] 5.53 29.32 1241.23 1.86 1243.09 ... 
    .. .. ..- attr(*, "names")= chr [1:11] "ldL2" "ldRX2" "wrss" "ussq" ... 
    .. ..$ dims: Named int [1:14] 1208 1208 5 1203 2 222 1 1 0 2 ... 
    .. .. ..- attr(*, "names")= chr [1:14] "N" "n" "p" "nmp" ... 
    [email protected] pp  :Reference class 'merPredD' [package "lme4"] with 18 fields 
    .. ..$ Lambdat:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. [email protected] i  : int [1:222] 0 1 2 3 4 5 6 7 8 9 ... 
    .. .. .. [email protected] p  : int [1:223] 0 1 2 3 4 5 6 7 8 9 ... 
    .. .. .. [email protected] Dim  : int [1:2] 222 222 
    .. .. .. [email protected] Dimnames:List of 2 
    .. .. .. .. ..$ : NULL 
    .. .. .. .. ..$ : NULL 
    .. .. .. [email protected] x  : num [1:222] 0 0 0 0 0 0 0 0 0 0 ... 
    .. .. .. [email protected] factors : list() 
    .. ..$ LamtUt :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. [email protected] i  : int [1:2416] 18 220 18 220 18 220 3 220 3 220 ... 
    .. .. .. [email protected] p  : int [1:1209] 0 2 4 6 8 10 12 14 16 18 ... 
    .. .. .. [email protected] Dim  : int [1:2] 222 1208 
    .. .. .. [email protected] Dimnames:List of 2 
    .. .. .. .. ..$ : NULL 
    .. .. .. .. ..$ : NULL 
    .. .. .. [email protected] x  : num [1:2416] 0 0.17 0 0.173 0 ... 
    .. .. .. [email protected] factors : list() 
    .. ..$ Lind : int [1:222] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ Ptr :<externalptr> 
    .. ..$ RZX : num [1:222, 1:5] 0 0 0 0 0 0 0 0 0 0 ... 
    .. ..$ Ut  :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. [email protected] i  : int [1:2416] 18 220 18 220 18 220 3 220 3 220 ... 
    .. .. .. [email protected] p  : int [1:1209] 0 2 4 6 8 10 12 14 16 18 ... 
    .. .. .. [email protected] Dim  : int [1:2] 222 1208 
    .. .. .. [email protected] Dimnames:List of 2 
    .. .. .. .. ..$ : chr [1:222] "GLQ_JB_58" "GLQ_JB_59" "GLQ_JB_60" "GLQ_JC_133" ... 
    .. .. .. .. ..$ : NULL 
    .. .. .. [email protected] x  : num [1:2416] 0.465 0.465 0.474 0.474 0.462 ... 
    .. .. .. [email protected] factors : list() 
    .. ..$ Utr : num [1:222] 0 0 0 0 0 0 0 0 0 0 ... 
    .. ..$ V  : num [1:1208, 1:5] 0.465 0.474 0.462 0.468 0.416 ... 
    .. ..$ VtV : num [1:5, 1:5] 241 0 0 0 0 ... 
    .. ..$ Vtr : num [1:5] 33.49 -15.03 34.71 8.54 512.19 
    .. ..$ X  : num [1:1208, 1:5] 1 1 1 1 1 1 1 1 1 1 ... 
    .. .. ..- attr(*, "dimnames")=List of 2 
    .. .. .. ..$ : chr [1:1208] "1" "2" "3" "4" ... 
    .. .. .. ..$ : chr [1:5] "(Intercept)" "PC1" "PC2" "PC3" ... 
    .. .. ..- attr(*, "assign")= int [1:5] 0 1 2 3 4 
    .. ..$ Xwts : num [1:1208] 0.465 0.474 0.462 0.468 0.416 ... 
    .. ..$ Zt  :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. [email protected] i  : int [1:2416] 18 220 18 220 18 220 3 220 3 220 ... 
    .. .. .. [email protected] p  : int [1:1209] 0 2 4 6 8 10 12 14 16 18 ... 
    .. .. .. [email protected] Dim  : int [1:2] 222 1208 
    .. .. .. [email protected] Dimnames:List of 2 
    .. .. .. .. ..$ : chr [1:222] "GLQ_JB_58" "GLQ_JB_59" "GLQ_JB_60" "GLQ_JC_133" ... 
    .. .. .. .. ..$ : NULL 
    .. .. .. [email protected] x  : num [1:2416] 1 1 1 1 1 1 1 1 1 1 ... 
    .. .. .. [email protected] factors : list() 
    .. ..$ beta0 : num [1:5] 0 0 0 0 0 
    .. ..$ delb : num [1:5] 0 0 0 0 0 
    .. ..$ delu : num [1:222] 0 0 0 0 0 0 0 0 0 0 ... 
    .. ..$ theta : num [1:2] 0 0.365 
    .. ..$ u0  : num [1:222] 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 
    [email protected] optinfo:List of 7 
    .. ..$ optimizer: chr "Nelder_Mead" 
    .. ..$ control :List of 3 
    .. .. ..$ xst : num [1:7] 0.02 0.02 0.0641 0.0122 0.0101 ... 
    .. .. ..$ xt  : num [1:7] 1.00e-05 1.00e-05 3.21e-05 6.10e-06 5.05e-06 ... 
    .. .. ..$ verbose: int 0 
    .. ..$ derivs :List of 2 
    .. .. ..$ gradient: num [1:7] 1.35e-03 -1.64e-04 -5.18e-05 -6.99e-04 8.31e-04 ... 
    .. .. ..$ Hessian : num [1:7, 1:7] 2.70e+02 5.34e-05 3.05e-05 -1.95e-03 -2.29e-05 ... 
    .. ..$ conv  :List of 2 
    .. .. ..$ opt : num 0 
    .. .. ..$ lme4: list() 
    .. ..$ feval : num 321 
    .. ..$ warnings : list() 
    .. ..$ val  : num [1:7] 0 0.365 -0.884 0.577 -0.143 ... 
> 
+0

MOD.MIX.1'的結構是什麼? – 2014-11-03 19:22:01

+0

edit added str(MOD.MIX.1) – user1658170 2014-11-03 19:29:35

+0

您的'newdata'數據框中沒有'Study_area'列 – 2014-11-03 19:55:28

回答

2

如果你想只使用固定效應(即不包括隨機效應)預測,那麼你需要包括「re.form = NA 「在代碼的預測行:

PREDICTPC1 < -predict(MOD.MIX.1,newdata,re.form = NA)

默認值在預測中包含隨機效果,在這種情況下,您需要一個指定「newdata」數據框中隨機效果的列,正如Robinson先生上文指出的那樣。

查看文檔http://www.inside-r.org/packages/cran/lme4/docs/predict.merMod