tests/testthat/test-association-mipred.cv.R

In mipred: Prediction using Multiple Imputation

context("association and output test")

skip('association tests mipred.cv')

cll <- readRDS("CLL_BMJ.rds")

cll_bin<-cll

cll_bin$srv5y_s[cll_bin$srv5y>12] <- 0  # Apply an administrative censorship at t=84 months
cll_bin$srv5y[cll_bin$srv5y>12]  <- 12

cll_bin$Status[cll_bin$srv5y_s==1]<- 1  # Define the "Status" variable
cll_bin$Status[cll_bin$srv5y_s==0] <- 0  # Ss numeric -> 1:Dead, 0:Alive

cll_bin$Censor <- NULL
cll_bin$srv5y <- NULL
cll_bin$srv5y_s <- NULL

# first check use of dot notation for both averaging and rubin method
# compare directly between full formula and dot notation calculation

# check for averaging method
# by comparing output between two distinct analyses
seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
  1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
  5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
  5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
  8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
  6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
  2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
  9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
  4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
  8229, 7099)+10000
seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:4]
set.seed(46409)
output1<-mipred.cv(Status~.,family=binomial,data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, printFlag=FALSE, seed=seed))
set.seed(46409)
output2<-mipred.cv(Status~age10+perfstat+remstat+cyto+asct+donor+sex_match+cond,family=binomial,data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, printFlag=FALSE, seed=seed))

test_that("mipred.cv results correct when using dot notation in predictor for averaging method",{
  expect_identical(output1[2:3],output2[2:3])
})


# check for rubin method
# by comparing output between two distinct analyses
seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
  1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
  5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
  5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
  8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
  6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
  2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
  9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
  4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
  8229, 7099)+10001
seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:4]
set.seed(45759)
output1<-mipred.cv(Status~.,family=binomial,data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, printFlag=FALSE, seed=seed), method="rubin")
set.seed(45759)
output2<-mipred.cv(Status~age10+perfstat+remstat+cyto+asct+donor+sex_match+cond,family=binomial,data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, printFlag=FALSE, seed=seed), method="rubin")

test_that("mipred.cv results correct when using dot notation in predictor for rubin method",{
  expect_identical(output1[2:3],output2[2:3])
})




# compare with saved results calculated from full formula
# based on: nimp=2, folds=2, mice.options=list(maxit=2, seed=seed) and seeds as below
# check for averaging method
preds <- structure(c(0.0913113982504282, 0.205002832411828, 0.235307753915466,
  0.130833369412761, 0.319891395664755, 0.413835233202078, 0.236344745128168,
  0.392046756922078, 0.264200646968459, 0.0772351029224595, 0.568917819972382,
  0.687785293948044, 0.319214856617008, 0.15487284715132, 0.145904144299823,
  0.0810923429069689, 0.0965360789590202, 0.545152140368265, 0.081994607086966,
  0.259873991202174, 0.338679002660538, 0.204087759931697, 0.315857454154808,
  0.243941811290267, 0.368990811322329, 0.377200109384867, 0.308414481997353,
  0.228459150501422, 0.323093985746204, 0.298826440413221, 0.330047776418152,
  0.151842578234661, 0.191419742683409, 0.23706732823784, 0.169729350412035,
  0.0990633395058016, 0.133251523440481, 0.100116154226906, 0.511138294559638,
  0.191705034407303, 0.297530636580443, 0.161762718389096, 0.243211039228653,
  0.245464776726281, 0.0491236604579135, 0.32234937345363, 0.426249681139407,
  0.259259736936139, 0.203364349892342, 0.206163879401658, 0.218196260387408,
  0.524342095569456, 0.307321840257096, 0.244507591094041, 0.0887639415190514,
  0.242688343448125, 0.11662653266584, 0.100097912347356, 0.484725694308464,
  0.165031354830531, 0.0841623230567649, 0.116974223431149, 0.558778531676977,
  0.209119493805785, 0.464177513783235, 0.239058713037548, 0.237683868841706,
  0.429513427704064, 0.180762257376498, 0.149169709418061, 0.30225122346481,
  0.201594283600267, 0.116986480237119, 0.252101634084587, 0.352275150192243,
  0.370772672400803, 0.316203935921901, 0.859546396955811, 0.365233550684307,
  0.240831531041877, 0.0918174522684127, 0.141506266644884, 0.0528347220955928,
  0.398520837467129, 0.190297167645349, 0.123522923207211, 0.127464627870317,
  0.395203908392914, 0.0869446168630749, 0.344548540783511, 0.167296508325157,
  0.198576943306381, 0.45788949892489, 0.288506739935992, 0.184533770940436,
  0.0553301989015827, 0.132880059042904, 0.187607721196768, 0.181747021755588,
  0.612135135665185, 0.321753854824794, 0.0490432503631617, 0.572619652077137,
  0.111464253200017, 0.251272587779984, 0.202412299007124, 0.345207017706479,
  0.289022736188874, 0.348644308147579, 0.222564494415229, 0.254858730172056,
  0.0550961636060158, 0.107730724305283, 0.366665418320996, 0.532006106764718,
  0.485684983922859, 0.0816121537299415, 0.13734029284154, 0.193004298159619,
  0.220630147964959, 0.324408101027024, 0.195529821072278, 0.192478978319568,
  0.157969224582182, 0.132669286738705, 0.0471418821922543, 0.129918578206572,
  0.27806798193113, 0.240541008837948, 0.283757777701297, 0.354605479086721,
  0.418171974881824, 0.311960603211056, 0.135152132774603, 0.285771695153382,
  0.172900037061388, 0.164197171820738, 0.105992684479298, 0.105725564999195,
  0.463763575088482, 0.186590468714341, 0.237961143306151, 0.278888829515329,
  0.689875204327845, 0.224072837960336, 0.483576081747667, 0.586351529180403,
  0.0795097024100417, 0.214720252675324, 0.484170936280297, 0.121472610875174,
  0.21430174127306, 0.0576060477060866, 0.118569003526581, 0.338714807316809,
  0.118903412143218, 0.0764112271500755, 0.0997845783687272, 0.25161826201572,
  0.114578295199989, 0.57434106494888, 0.3289518997789, 0.285230258274293,
  0.228774932691599, 0.0535670170066243, 0.183721210771269, 0.406632843837022,
  0.19860211153078, 0.122899662172889, 0.610878583352401, 0.508642129930739,
  0.234496750310723, 0.298640272842297, 0.114655222184175, 0.25994313293533,
  0.261861241448966, 0.439142254879224, 0.212035101505423, 0.0649605393137098,
  0.120066837044841, 0.269503278694515, 0.352640269571813, 0.189705351946428,
  0.174280694089135, 0.147530550220686, 0.187147133787329, 0.126377208146948,
  0.0849568133655036, 0.361924502503413, 0.194950885797577, 0.565500624582376,
  0.626757216993373, 0.280996998258359, 0.467373589234425, 0.089123016741405,
  0.160811937382287, 0.241120652619818, 0.093101126573148, 0.596296190651742,
  0.638358966881976, 0.143503176309917, 0.264720025633886, 0.177463324376691,
  0.458149589386367, 0.167864124437393, 0.0866715110428221, 0.118996197942772,
  0.522391688354131, 0.160377062510365, 0.272849246118406, 0.150109988826045,
  0.0910543221001234, 0.390184108307785, 0.242385145123559, 0.114782432232922,
  0.13663952861347, 0.228270313470934, 0.39006380808953, 0.146513359579913,
  0.235004173393785, 0.557703650607244, 0.142471192223014, 0.453087897635295,
  0.152930060686964, 0.0723649724685446, 0.135956229349844, 0.202819836121764,
  0.503100708371882, 0.253950777098664, 0.0639327236859717, 0.102075681079699,
  0.108828083651577, 0.147606315408737, 0.0839489440523298, 0.396978429618175,
  0.43980785099197, 0.295741952968536, 0.24866910935347, 0.0442467487809289,
  0.335596563093868, 0.233228866477628, 0.133393318755783, 0.284416207171384,
  0.29140518658153, 0.234880226397143, 0.457838300826364, 0.085230830081924,
  0.423792672995716, 0.290795292528064, 0.0475246191577339, 0.182186335835526,
  0.0688766646362923, 0.219799288309372, 0.177225736452385, 0.214875117617374,
  0.148250107443774, 0.205771584644564, 0.137090663919187, 0.356839693410918,
  0.0735180962587929, 0.264633845299221, 0.205826996579185, 0.425245070405229,
  0.633954688139198, 0.29016632329167, 0.0765409371741137, 0.134470496708206,
  0.100724087501366, 0.355784892571077, 0.78477762599775, 0.230576639362723,
  0.302412966289922, 0.504181632055426, 0.309466340699462, 0.191066673047739,
  0.08004651339456, 0.288757012835596, 0.285042629519114, 0.112755987625244,
  0.267087791856027, 0.0508230077902539, 0.345929716560103, 0.637125966042463,
  0.180899944820286, 0.215332187714617, 0.251182879706532, 0.319201486399136,
  0.367696438151064, 0.180788629752681, 0.13849551153464, 0.666105739245672,
  0.244973476068862, 0.111196694120228, 0.294620201386095, 0.227131143776411,
  0.0729252481424116, 0.133122735769919, 0.492318629494797, 0.24576521392074,
  0.115089280792056, 0.310689889215603, 0.135301319268956, 0.367358683333803,
  0.219365120052191, 0.221021672619675, 0.279014472009185, 0.139560855135115,
  0.424644897533196, 0.381278983854846, 0.134110214153216, 0.0428133011354741,
  0.245011035601121, 0.102771641756052, 0.248637079011597, 0.173037250737929,
  0.345878030376164, 0.214376464837771, 0.189603551924222, 0.326773800666793,
  0.524773362585224, 0.264061093723736, 0.306529390368926, 0.391848286436733,
  0.168395429160241, 0.0758089753003229, 0.114146280894431, 0.226801443836648,
  0.0554744498338692, 0.228945339608141, 0.342728148402927, 0.193992218315681,
  0.138015739480982, 0.18904233547156, 0.265549405496245, 0.20662261872852,
  0.194439085207122, 0.117931050755386, 0.172984547683882, 0.252764307026127,
  0.311889340153156, 0.168566354554529, 0.557329086228746, 0.182674721644917,
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  0.104513312355488, 0.300544245312882, 0.178321376256338, 0.517639890333677,
  0.493602740959582, 0.280036333329485, 0.230387868264402, 0.113566308691069,
  0.220093592507994, 0.119667102465718, 0.11504603472064, 0.229525065523036,
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  0.180428587976545, 0.196907760642303, 0.220040922678855, 0.18707271401047,
  0.182398239854685, 0.126366363019106, 0.127072044570986, 0.172802094924319,
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    "200", "201", "202", "203", "204", "205", "206", "207", "208",
    "209", "210", "211", "212", "213", "214", "215", "216", "217",
    "218", "219", "220", "221", "222", "223", "224", "225", "226",
    "227", "228", "229", "230", "231", "232", "233", "234", "235",
    "236", "237", "238", "239", "240", "241", "242", "243", "244",
    "245", "246", "247", "248", "249", "250", "251", "252", "253",
    "254", "255", "256", "257", "258", "259", "260", "261", "262",
    "263", "264", "265", "266", "267", "268", "269", "270", "271",
    "272", "273", "274", "275", "276", "277", "278", "279", "280",
    "281", "282", "283", "284", "285", "286", "287", "288", "289",
    "290", "291", "292", "293", "294", "295", "296", "297", "298",
    "299", "300", "301", "302", "303", "304", "305", "306", "307",
    "308", "309", "310", "311", "312", "313", "314", "315", "316",
    "317", "318", "319", "320", "321", "322", "323", "324", "325",
    "326", "327", "328", "329", "330", "331", "332", "333", "334",
    "335", "336", "337", "338", "339", "340", "341", "342", "343",
    "344", "345", "346", "347", "348", "349", "350", "351", "352",
    "353", "354", "355", "356", "357", "358", "359", "360", "361",
    "362", "363", "364", "365", "366", "367", "368", "369", "370",
    "371", "372", "373", "374", "375", "376", "377", "378", "379",
    "380", "381", "382", "383", "384", "385", "386", "387", "388",
    "389", "390", "391", "392", "393", "394", "395", "396", "397",
    "398", "399", "400", "401", "402", "403", "404", "405", "406",
    "407", "408", "409", "410", "411", "412", "413", "414", "415",
    "416", "417", "418", "419", "420", "421", "422", "423", "424",
    "425", "426", "427", "428", "429", "430", "431", "432", "433",
    "434", "435", "436", "437", "438", "439", "440", "441", "442",
    "443", "444", "445", "446", "447", "448", "449", "450", "451",
    "452", "453", "454", "455", "456", "457", "458", "459", "460",
    "461", "462", "463", "464", "465", "466", "467", "468", "469",
    "470", "471", "472", "473", "474", "475", "476", "477", "478",
    "479", "480", "481", "482", "483", "484", "485", "486", "487",
    "488", "489", "490", "491", "492", "493", "494", "495", "496",
    "497", "498", "499", "500", "501", "502", "503", "504", "505",
    "506", "507", "508", "509", "510", "511", "512", "513", "514",
    "515", "516", "517", "518", "519", "520", "521", "522", "523",
    "524", "525", "526", "527", "528", "529", "530", "531", "532",
    "533", "534", "535", "536", "537", "538", "539", "540", "541",
    "542", "543", "544", "545", "546", "547", "548", "549", "550",
    "551", "552", "553", "554", "555", "556", "557", "558", "559",
    "560", "561", "562", "563", "564", "565", "566", "567", "568",
    "569", "570", "571", "572", "573", "574", "575", "576", "577",
    "578", "579", "580", "581", "582", "583", "584", "585", "586",
    "587", "588", "589", "590", "591", "592", "593", "594", "595",
    "596", "597", "598", "599", "600", "601", "602", "603", "604",
    "605", "606", "607", "608", "609", "610", "611", "612", "613",
    "614", "615", "616", "617", "618", "619", "620", "621", "622",
    "623", "624", "625", "626", "627", "628", "629", "630", "631",
    "632", "633", "634", "635", "636", "637", "638", "639", "640",
    "641", "642", "643", "644", "645", "646", "647", "648", "649",
    "650", "651", "652", "653", "654", "655", "656", "657", "658",
    "659", "660", "661", "662", "663", "664", "665", "666", "667",
    "668", "669", "670", "671", "672", "673", "674", "675", "676",
    "677", "678", "679", "680", "681", "682", "683", "684", "685",
    "686", "687", "688", "689", "690", "691", "692", "693", "694"
  ), NULL))


seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
  1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
  5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
  5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
  8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
  6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
  2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
  9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
  4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
  8229, 7099)
seed <- as.vector(matrix(seeds,ncol=1))
set.seed(54321)
# code shown how preds is generated
# output<-mipred.cv(Status~age10+perfstat+remstat+cyto+asct+donor+sex_match+cond,family=binomial(link="logit"),data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, seed=seed))
# now try replicate using dot notation
output<-mipred.cv(Status~.,family=binomial(link="logit"),data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, seed=seed))

test_that("predictions replicate from saved results generated with full formula when using dot notation for averaging approach in mipred.cv",{
  expect_equal(output$pred,preds)
})

# based on: nimp=2, folds=2, mice.options=list(maxit=2, seed=seed) and seeds as below
# check for rubin method
preds <- structure(c(0.112516236188612, 0.268729786968734, 0.229765573394903,
  0.123467553114857, 0.526660968626616, 0.316647944272368, 0.248045102969626,
  0.443563798460693, 0.239073489349524, 0.075790993993578, 0.556186320307558,
  0.644400737976303, 0.331901957618878, 0.256481033938746, 0.207746057428202,
  0.0883205037326528, 0.0836283671188999, 0.72374834964979, 0.123852768385256,
  0.171095232694986, 0.371179212762646, 0.169529079592908, 0.148641121251324,
  0.246124527159818, 0.204831978107602, 0.371469661868614, 0.29895072995226,
  0.24003539843697, 0.301911938764166, 0.268176132818944, 0.402730012515681,
  0.123203217690244, 0.175382813522824, 0.243787202935133, 0.154570743743053,
  0.11513382871577, 0.0892703602703067, 0.173503228668694, 0.586906287013078,
  0.190188017537089, 0.231439863206969, 0.148145045386993, 0.263867554763507,
  0.194147412810803, 0.0641298855195087, 0.274965081474535, 0.330360829599618,
  0.22228089900444, 0.196687309685874, 0.21355851029492, 0.253772310545182,
  0.552973717230694, 0.839524183217672, 0.248151740895107, 0.0799917039906281,
  0.292619523421717, 0.102061667471168, 0.116300739823087, 0.487271526250492,
  0.165294657729144, 0.0741457637995324, 0.132731037822674, 0.450259780331514,
  0.227589951441161, 0.415504677877886, 0.21841250553427, 0.245517243280248,
  0.267346300124381, 0.189617995152404, 0.15730277285272, 0.283507950836482,
  0.203256123932201, 0.101925471793757, 0.337603012030191, 0.306444145137839,
  0.322285342284345, 0.336062485191841, 0.884395859363546, 0.516983512562526,
  0.286248918825726, 0.0977350374316844, 0.111323613619882, 0.11037526042358,
  0.329995384151483, 0.188174243208545, 0.162051400659548, 0.128070231774751,
  0.347882605778437, 0.0921476034032863, 0.304594466552665, 0.149887438525528,
  0.216660507950277, 0.409577205955607, 0.227848593428249, 0.650247908088443,
  0.051437993418339, 0.139156836261922, 0.170901661442288, 0.20089854551342,
  0.628408478031471, 0.337719571874079, 0.0795358916256249, 0.54872462681998,
  0.112180332275013, 0.273454817692222, 0.213289145128453, 0.392271365686654,
  0.280456711214445, 0.192620593530291, 0.19103103729081, 0.1406732498904,
  0.0515938072536092, 0.0992236521220728, 0.297100582057062, 0.521855848286837,
  0.433083027837868, 0.149056845921899, 0.462806532181737, 0.308548605313264,
  0.179559883501593, 0.330925575740609, 0.219610123139958, 0.15879872770383,
  0.166895012300544, 0.121100499363444, 0.0772859235710661, 0.131860935844565,
  0.278070387872065, 0.21174300357043, 0.230132422760407, 0.326354232425632,
  0.370375111733958, 0.244755248962374, 0.126954461842776, 0.250371761861621,
  0.160219492798746, 0.231564519009254, 0.108545017286106, 0.1742806524866,
  0.516491510538509, 0.158205880878487, 0.29624527679747, 0.333596615741652,
  0.735711531383683, 0.228682172791014, 0.283636946264991, 0.523926223662838,
  0.0817930349482075, 0.355353636087258, 0.474565760327317, 0.107096478986007,
  0.198371964459408, 0.0626068163293693, 0.133606410695916, 0.318266704685804,
  0.150596295096059, 0.0952922359572668, 0.0921085213896791, 0.263785276551806,
  0.12465158729642, 0.557633890780449, 0.423992275157417, 0.238233511786778,
  0.11579783836653, 0.0636761955233425, 0.198019367085348, 0.22895634077193,
  0.269471034801686, 0.115986994435872, 0.803694979980046, 0.500143378133316,
  0.281386609351861, 0.331729922356322, 0.106677524215197, 0.272156575441057,
  0.204931195746242, 0.487782009319744, 0.140551843774873, 0.0616420415660063,
  0.252503544431739, 0.239510913524556, 0.307767356625899, 0.19121777178748,
  0.136762283339135, 0.157415476097511, 0.166864247519057, 0.133895671112361,
  0.0924450876046859, 0.32102858763536, 0.198895123946026, 0.527380390585718,
  0.585459540589679, 0.286672434945698, 0.505852630660537, 0.0821321454747653,
  0.181649432672358, 0.226487500756802, 0.147822753589431, 0.60158174893537,
  0.249533883109669, 0.263829435915395, 0.30709593026273, 0.139967519094007,
  0.42243543014036, 0.148522862226092, 0.0989773823239199, 0.116359333932108,
  0.463839925806043, 0.146782842329972, 0.267622375036728, 0.200363056364067,
  0.0857930601179574, 0.354460330559097, 0.231102616157033, 0.105913323480747,
  0.167158425717844, 0.178303701058023, 0.647966256774878, 0.124741103617379,
  0.232292520456271, 0.582934657835532, 0.127887054196021, 0.500799986958398,
  0.144106700014086, 0.0653016501695146, 0.151720165761754, 0.191985147537726,
  0.474596508907523, 0.254545759628035, 0.0763650291460135, 0.0415779169508906,
  0.105898133489484, 0.110183466703419, 0.109137695669127, 0.351594735987558,
  0.445828232051039, 0.189002510222596, 0.111066974140196, 0.0692409710447151,
  0.19031340965407, 0.258575911893777, 0.16675089027811, 0.282931007612389,
  0.228876648204738, 0.215928311370215, 0.423293992592713, 0.10015495383643,
  0.486496091019948, 0.337052467270748, 0.0571699897283551, 0.196677293947185,
  0.0927625753817313, 0.23717788867509, 0.206581860941913, 0.232189257685112,
  0.17568409275671, 0.284339636051452, 0.132429128154783, 0.32428200715764,
  0.0727979243370251, 0.237000421818326, 0.223728864510441, 0.373420309430876,
  0.660721085356123, 0.186863750505186, 0.091132421917107, 0.16580678654138,
  0.0913288672917396, 0.358202791896484, 0.801673150101103, 0.270463780334883,
  0.275575410882529, 0.511834470439226, 0.276829106009443, 0.178935709165406,
  0.0629845051086953, 0.296467111997119, 0.310813241871184, 0.0680707532238572,
  0.232492541797476, 0.0481822617476797, 0.423867968593386, 0.49365692565396,
  0.181202315668459, 0.561529634391357, 0.146844383988175, 0.392248045492012,
  0.323103499505407, 0.227478951627676, 0.113538103187433, 0.698995268580352,
  0.228061852040656, 0.0562052200744133, 0.278997780473528, 0.232584220044108,
  0.071237818425445, 0.203841300534297, 0.440749349043022, 0.302467959444009,
  0.145987578449451, 0.301612486577209, 0.13522783244574, 0.393858232834414,
  0.243014400924523, 0.190532298995412, 0.174201903130375, 0.157460385165891,
  0.436546378954301, 0.367697102815664, 0.151502862013241, 0.0511353950804288,
  0.236867879442464, 0.11295276423114, 0.295189817668446, 0.178573804972732,
  0.510465304323057, 0.201490070955628, 0.145143696925069, 0.32167765539439,
  0.524110663283354, 0.232266827394817, 0.328013022408512, 0.293712527336582,
  0.211508788090533, 0.0652301533116838, 0.111440953610875, 0.1387357635709,
  0.0742743722877095, 0.248372110342705, 0.315421215175118, 0.222695532719943,
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  0.424111653814498, 0.43141697689482, 0.287103788312654, 0.293660813747509,
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  0.144390793839118, 0.265994000074135, 0.155879545607843, 0.484200123795378,
  0.534680909274378, 0.389849315887292, 0.211587991920211, 0.110293428251396,
  0.190300641382238, 0.111328639513459, 0.107018210215805, 0.212592664659291,
  0.345709137496685, 0.349654322324745, 0.197355625608947, 0.216555102556539,
  0.19207816468319, 0.165487095550521, 0.242014589131367, 0.254935549287185,
  0.358189711667039, 0.284321125834299, 0.266078565513548, 0.312473094451968,
  0.535494604134233, 0.186301015388116, 0.104193277884679, 0.40816920551436,
  0.114518787849035, 0.456230552053034, 0.0812366919138023, 0.125802607443974,
  0.0748479651078767, 0.0985958498445323, 0.342635116755968, 0.308275450938105,
  0.207744472147645, 0.178899439953629, 0.20187611965575, 0.16458454203278,
  0.223628575981823, 0.10896076543035, 0.283505663228442, 0.15207002307647,
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  0.0641967468580518, 0.0961920989024718, 0.332231256992119, 0.779756912195156,
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  0.0881120683223164, 0.214777199326945, 0.154666597961513, 0.173236417067128,
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  0.391134852683023, 0.214161232063759, 0.202250463746677, 0.251959701176844,
  0.0794635134524419, 0.315878264857548, 0.169570771903896, 0.682302826550195,
  0.467746325632325, 0.32260161357416, 0.620710594713183, 0.356895956314686,
  0.428584525492461, 0.532089087583444, 0.353190308643947, 0.268914305170133,
  0.334983957242072), .Dim = c(694L, 2L), .Dimnames = list(c("1",
    "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
    "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
    "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35",
    "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46",
    "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57",
    "58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68",
    "69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79",
    "80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90",
    "91", "92", "93", "94", "95", "96", "97", "98", "99", "100",
    "101", "102", "103", "104", "105", "106", "107", "108", "109",
    "110", "111", "112", "113", "114", "115", "116", "117", "118",
    "119", "120", "121", "122", "123", "124", "125", "126", "127",
    "128", "129", "130", "131", "132", "133", "134", "135", "136",
    "137", "138", "139", "140", "141", "142", "143", "144", "145",
    "146", "147", "148", "149", "150", "151", "152", "153", "154",
    "155", "156", "157", "158", "159", "160", "161", "162", "163",
    "164", "165", "166", "167", "168", "169", "170", "171", "172",
    "173", "174", "175", "176", "177", "178", "179", "180", "181",
    "182", "183", "184", "185", "186", "187", "188", "189", "190",
    "191", "192", "193", "194", "195", "196", "197", "198", "199",
    "200", "201", "202", "203", "204", "205", "206", "207", "208",
    "209", "210", "211", "212", "213", "214", "215", "216", "217",
    "218", "219", "220", "221", "222", "223", "224", "225", "226",
    "227", "228", "229", "230", "231", "232", "233", "234", "235",
    "236", "237", "238", "239", "240", "241", "242", "243", "244",
    "245", "246", "247", "248", "249", "250", "251", "252", "253",
    "254", "255", "256", "257", "258", "259", "260", "261", "262",
    "263", "264", "265", "266", "267", "268", "269", "270", "271",
    "272", "273", "274", "275", "276", "277", "278", "279", "280",
    "281", "282", "283", "284", "285", "286", "287", "288", "289",
    "290", "291", "292", "293", "294", "295", "296", "297", "298",
    "299", "300", "301", "302", "303", "304", "305", "306", "307",
    "308", "309", "310", "311", "312", "313", "314", "315", "316",
    "317", "318", "319", "320", "321", "322", "323", "324", "325",
    "326", "327", "328", "329", "330", "331", "332", "333", "334",
    "335", "336", "337", "338", "339", "340", "341", "342", "343",
    "344", "345", "346", "347", "348", "349", "350", "351", "352",
    "353", "354", "355", "356", "357", "358", "359", "360", "361",
    "362", "363", "364", "365", "366", "367", "368", "369", "370",
    "371", "372", "373", "374", "375", "376", "377", "378", "379",
    "380", "381", "382", "383", "384", "385", "386", "387", "388",
    "389", "390", "391", "392", "393", "394", "395", "396", "397",
    "398", "399", "400", "401", "402", "403", "404", "405", "406",
    "407", "408", "409", "410", "411", "412", "413", "414", "415",
    "416", "417", "418", "419", "420", "421", "422", "423", "424",
    "425", "426", "427", "428", "429", "430", "431", "432", "433",
    "434", "435", "436", "437", "438", "439", "440", "441", "442",
    "443", "444", "445", "446", "447", "448", "449", "450", "451",
    "452", "453", "454", "455", "456", "457", "458", "459", "460",
    "461", "462", "463", "464", "465", "466", "467", "468", "469",
    "470", "471", "472", "473", "474", "475", "476", "477", "478",
    "479", "480", "481", "482", "483", "484", "485", "486", "487",
    "488", "489", "490", "491", "492", "493", "494", "495", "496",
    "497", "498", "499", "500", "501", "502", "503", "504", "505",
    "506", "507", "508", "509", "510", "511", "512", "513", "514",
    "515", "516", "517", "518", "519", "520", "521", "522", "523",
    "524", "525", "526", "527", "528", "529", "530", "531", "532",
    "533", "534", "535", "536", "537", "538", "539", "540", "541",
    "542", "543", "544", "545", "546", "547", "548", "549", "550",
    "551", "552", "553", "554", "555", "556", "557", "558", "559",
    "560", "561", "562", "563", "564", "565", "566", "567", "568",
    "569", "570", "571", "572", "573", "574", "575", "576", "577",
    "578", "579", "580", "581", "582", "583", "584", "585", "586",
    "587", "588", "589", "590", "591", "592", "593", "594", "595",
    "596", "597", "598", "599", "600", "601", "602", "603", "604",
    "605", "606", "607", "608", "609", "610", "611", "612", "613",
    "614", "615", "616", "617", "618", "619", "620", "621", "622",
    "623", "624", "625", "626", "627", "628", "629", "630", "631",
    "632", "633", "634", "635", "636", "637", "638", "639", "640",
    "641", "642", "643", "644", "645", "646", "647", "648", "649",
    "650", "651", "652", "653", "654", "655", "656", "657", "658",
    "659", "660", "661", "662", "663", "664", "665", "666", "667",
    "668", "669", "670", "671", "672", "673", "674", "675", "676",
    "677", "678", "679", "680", "681", "682", "683", "684", "685",
    "686", "687", "688", "689", "690", "691", "692", "693", "694"
  ), NULL))


seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
  1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
  5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
  5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
  8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
  6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
  2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
  9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
  4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
  8229, 7099)
seed <- as.vector(matrix(seeds,ncol=1))
set.seed(54321)
# code shown how preds is generated
# output<-mipred.cv(Status~age10+perfstat+remstat+cyto+asct+donor+sex_match+cond,family=binomial(link="logit"),data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, seed=seed), method="rubin")
# now try replicate using dot notation
output<-mipred.cv(Status~.,family=binomial(link="logit"),data=cll_bin[1:694,-1], nimp=2, folds=2, mice.options=list(maxit=2, seed=seed), method="rubin")

test_that("predictions replicate from saved results generated with full formula when using dot notation for rubin approach in mipred.cv",{
  #  expect_identical(abs(cor(apply(output$pred,1,mean),preds)-0.979144406319983)<1e-13)
  expect_equal(output$pred,preds)
})