R 假不完整案例 数据型号

如何解决R 假不完整案例 数据型号

当数据中没有“NA”时，我遇到了一个声称有“不完整案例”的数据库的问题。

数据

data <- structure(list(`Module #` = structure(c(1L,1L,2L,3L,4L,5L,6L,7L,8L,9L,10L,11L,12L,12L),.Label = c("111","112","113","114","115","116","211","212","213","214","215","216"),class = "factor"),TimeStep = structure(c(1L,.Label = c("1","2","3","4","5","6","7","8","9","10","11","12"),`Taxonomic Code` = c("PC","PC","PC"),Site_long = structure(c(2L,1L),.Label = c("Hanauma Bay","Waikiki"),Shelter = structure(c(2L,.Label = c("Low","High"
    ),class = c("ordered","factor")),Year = structure(c(1L,NA,4L),.Label = c("17","18","19","20"),Season = structure(c(1L,.Label = c("summer","fall","winter","spring"),recruits = c(1,9,2,4,15,12,5,3,1,35,8,6,7,11,14,10,20,13,16,22,5),Settlement_Area = c(1.199256896,1.199256896,1.13816975,1.124678109,1.048225482,1.149038015,0.889323945,0.84772472,1.098069597,1.050099321,1.131798697,0.974770998,1.065090032,1.195509219,1.195883986,1.052347927,1.008500097,1.075583531,1.195883988,1.162904422,1.111186471,1.188388632,1.19363538,1.197757825,1.002503812,1.109687398,0.975520533,1.191386773,0.906938029,0.8293611,1.085327493,1.065839567,0.954908305,0.877706141,0.879205215,1.010748704,0.766025344,0.818492832,0.768648717,0.927550256,0.855969613,0.752533704,0.819242369,0.872459394,1.160281048,1.148663247,1.000629974,1.025739415,0.940292361,1.048975018,1.147538942,0.933921309,0.731546706,0.677954916,0.82411435,0.662589436,0.707936338,0.625862193,0.70943541,1.165527798,1.182017581,1.017494524,1.119056591,1.198507361,1.03848152,1.194010148,0.967650408,0.935795148,0.918930598,1.10931263),recruits_per_meter_squared = c(0.833849697538033,7.50464727784229,1.66769939507607,3.33539879015213,13.1790534759863,10.6697195437277,3.81597286908925,4.35146612620993,3.37334895441278,2.35925643409337,2.5015490926141,0.833849697538033,4.16924848769016,4.55344544067183,29.1847394138311,2.85687262148034,7.06839477833398,3.07764593546104,5.0030981852282,5.83694788276623,9.20110010460739,2.50860454284902,2.85076819465241,4.95785772839643,5.57836730209288,11.6738957655325,6.68961210307634,2.57974769314275,6.29957273840855,9.25623125617378,5.86443742979535,8.33849697538033,1.66978662819423,9.17234667291836,16.6769939507607,9.9750244141715,6.30808281018255,2.51807395212705,1.20574741207419,3.68552351783094,3.75291002871917,1.13933348906579,14.7860815407015,1.97873120399272,6.52719918363432,6.10878898937016,8.62486959412795,2.336531542271,1.32884413639499,2.44127998707059,10.3423218199458,6.09404019696993,3.99748169046953,10.7239712534591,15.252984795106,8.7143012180235,2.14150804861869,1.47502433627902,9.70739072799788,1.50923021960163,1.41255639288854,7.98897913298303,4.22871477475307,6.67079758030426,10.0061963704564,18.8755686803448,5.07606663085665,0.982806272085647,2.68082957030723,5.00622707481227,6.74061104139821,13.4002211177187,4.13372429436313,1.06860994325224,7.61755024289658,4.50729565749197),recruits_per_meter_squared_trans = c(0.606417417116062,2.14061275265888,0.981216451194359,1.46681359911608,2.6517657682404,2.45699741376699,1.57193807449589,1.67737056564742,1.47552906673462,1.21171965010782,1.25320546846756,0.606417417116062,1.64272731773985,1.71441853526271,3.40733647924214,1.34985665339693,2.08795455026992,1.40551984529833,1.79227570016263,1.92234141608064,2.32249556786735,1.25521839228753,1.34827265947456,1.78471097491844,1.88378658416677,2.53954442659202,2.03987034051273,1.27529232115324,1.98781581745633,2.32788544830298,1.92635408827215,2.23414531588437,0.981998554684824,2.31967292807609,2.87226401734407,2.39562218348464,1.98898096989416,1.25791366716522,0.791066413855957,1.54447765284797,1.55875706808582,0.760494326814406,2.75912863665368,1.09149743937909,2.01852301825499,1.9613319043251,2.26435033142003,1.20493180701712,0.845372065689377,1.23584349144197,2.42854102336897,1.95925502266889,1.60893412364774,2.46163557090596,2.78827657160752,2.27359915209253,1.14470295488804,0.90625022881232,2.37093422527184,0.919976020688425,0.880686929248391,2.19599928619387,1.65416550691258,2.03742059697475,2.398458420606,2.98949127297859,1.8043575509105,0.684513150406024,1.30313815348998,1.79279677684048,2.04648063040265,2.66724356186119,1.63583137909093,0.726876856704456,2.15380084972511,1.7060736964172)),row.names = c(NA,-144L
),groups = structure(list(`Module #` = structure(c(1L,.rows = structure(list(1L,13L,14L,15L,16L,17L,18L,19L,20L,21L,22L,23L,24L,25L,26L,27L,28L,29L,30L,31L,32L,33L,34L,35L,36L,37L,38L,39L,40L,41L,42L,43L,44L,45L,46L,47L,48L,49L,50L,51L,52L,53L,54L,55L,56L,57L,58L,59L,60L,61L,62L,63L,64L,65L,66L,67L,68L,69L,70L,71L,72L,73L,74L,75L,76L,77L,78L,79L,80L,81L,82L,83L,84L,85L,86L,87L,88L,89L,90L,91L,92L,93L,94L,95L,96L,97L,98L,99L,100L,101L,102L,103L,104L,105L,106L,107L,108L,109L,110L,111L,112L,113L,114L,115L,116L,117L,118L,119L,120L,121L,122L,123L,124L,125L,126L,127L,128L,129L,130L,131L,132L,133L,134L,135L,136L,137L,138L,139L,140L,141L,142L,143L,144L),ptype = integer(0),class = c("vctrs_list_of","vctrs_vctr","list"))),class = c("tbl_df","tbl","data.frame"),.drop = TRUE),class = c("grouped_df","tbl_df","data.frame"))

型号

################## lm original
# all corals with sides combined
# with interaction
data$Site_long <- as.factor(data$Site_long)
# factorize variables

data$Season <- as.factor(data$Season)
data$Season <-  factor(data$Season,levels = c("summer",ordered = TRUE) 
season <- data$Season
data$Shelter <- factor(data$Shelter,levels = c("Low","High"),ordered = TRUE)


recruitment_lm_original <- lmer(recruits_per_meter_squared_trans ~ Site_long*Shelter + (1|Year/Season),data = data,na.action = "na.fail")
summary(recruitment_lm_original)

在此数据库上运行 lmer 时，出现以下错误：

"na.fail.default(list(recruits_per_meter_squared_trans = c(0.606417417116062,: 对象中的缺失值"

当我查看数据库中完整案例的数量与存在的行数时，行数存在差异：

nrow(data)

nrow(data[complete.cases(data),])

nrow(数据) [1] 144

nrow(data[complete.cases(data),]) [1] 139

在这里您可以看到完整行数与总行数之间存在差异。尽管数据库中没有“NA”，但情况仍然如此。我希望能够运行我的模型，同时确保处理所有 144 行，而不是 139 行。因为我想在这个模型上使用 MuMin::dredge() 函数，所以我需要使用 na.action = "na.失败”参数在 lmer() 中。这里发生了什么？提前致谢！