R 检查每个条件下是否有每个参与者的数据

我有一个数据集，其中包括每个参与者的多个试验。试验分布在受试者因素范围内

如果我决定删除基于平均值标准偏差的试验（仅举一个例子，我从平均值中知道sd很糟糕），那么对于一些参与者来说，一种情况下的所有值都可能被删除。如果是这样，我想从数据帧中删除整个参与者

#This dataframe is the dataframe above, but aggregated by participant.
df3 <- structure(list(`seq.int(nrow(df_aggregated))` = 1:6, X = c(105.151515151515, 
109.636363636364, 291.4, 275.655172413793, 390.888888888889, 
394.142857142857), participant = c(31, 31, 32, 32, 33, 33), latency = c(1.41229685445455, 
1.49138069215152, 1.15693726156887, 1.13918565853005, 1.29780718926878, 
1.13749230851929), Group = c(1, 2, 1, 2, 1, 2)), class = "data.frame", row.names = c(NA, 
-6L))
#here, the code correctly identifies that there is data for each condition of each participant and includes it in the final dataframe.
groups <- aggregate(
  Group ~ participant,
  df3,
  function(x) identical(sort(unique(x)), unique(df3$Group))
)

compliant_participants <- groups[which(groups$Group),][["participant"]]
data_cleaned <- df3[df3$participant %in% compliant_participants,]

简而言之，我要寻找的是：如果每个条件中都有一个值，那么将参与者复制到最终的数据帧。如果一个条件中没有值，则从数据帧中删除整个参与者

#This dataframe is the dataframe above, but aggregated by participant.
df3 <- structure(list(`seq.int(nrow(df_aggregated))` = 1:6, X = c(105.151515151515, 
109.636363636364, 291.4, 275.655172413793, 390.888888888889, 
394.142857142857), participant = c(31, 31, 32, 32, 33, 33), latency = c(1.41229685445455, 
1.49138069215152, 1.15693726156887, 1.13918565853005, 1.29780718926878, 
1.13749230851929), Group = c(1, 2, 1, 2, 1, 2)), class = "data.frame", row.names = c(NA, 
-6L))
#here, the code correctly identifies that there is data for each condition of each participant and includes it in the final dataframe.
groups <- aggregate(
  Group ~ participant,
  df3,
  function(x) identical(sort(unique(x)), unique(df3$Group))
)

compliant_participants <- groups[which(groups$Group),][["participant"]]
data_cleaned <- df3[df3$participant %in% compliant_participants,]

请在下面找到一些代码不起作用的数据，然后是一些代码起作用的数据

dfn <- structure(list(X = c(11L, 12L, 18L, 20L, 27L, 29L, 33L, 36L, 
37L, 47L, 51L, 55L, 57L, 58L, 61L, 68L, 71L, 76L, 77L, 78L, 80L, 
84L, 86L, 87L, 90L, 92L, 95L, 98L, 100L, 101L, 103L, 106L, 109L, 
114L, 116L, 117L, 119L, 122L, 123L, 130L, 131L, 132L, 136L, 138L, 
140L, 141L, 143L, 144L, 146L, 147L, 149L, 154L, 158L, 160L, 161L, 
163L, 167L, 168L, 169L, 170L, 174L, 177L, 178L, 180L, 182L, 186L, 
193L, 195L, 196L, 197L, 198L, 200L, 201L, 203L, 204L, 205L, 206L, 
209L, 210L, 213L, 215L, 216L, 217L, 218L, 220L, 222L, 224L, 226L, 
227L, 229L, 230L, 231L, 232L, 234L, 238L, 239L, 240L, 241L, 242L, 
246L, 249L, 251L, 252L, 253L, 254L, 255L, 256L, 260L, 261L, 262L, 
263L, 266L, 267L, 269L, 271L, 272L, 273L, 274L, 275L, 276L, 279L, 
280L, 282L, 284L, 285L, 286L, 287L, 288L, 289L, 291L, 293L, 294L, 
295L, 298L, 300L, 301L, 304L, 305L, 306L, 308L, 309L, 311L, 312L, 
313L, 315L, 316L, 318L, 319L, 320L, 321L, 324L, 325L, 326L, 327L, 
328L, 330L, 331L, 332L, 333L, 334L, 336L, 339L, 340L, 341L, 342L, 
344L, 345L, 347L, 348L, 349L, 350L, 353L, 354L, 356L, 357L, 358L, 
360L, 362L, 366L, 368L, 369L, 370L, 371L, 372L, 379L, 380L, 381L, 
384L, 385L, 387L, 388L, 389L, 392L, 395L, 399L, 401L, 402L, 404L, 
405L, 406L), participant = c(31L, 31L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 
32L, 32L, 32L, 32L, 32L, 32L, 32L, 32L, 33L, 33L, 33L, 33L, 33L, 
33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 33L), latency = c(1.241730792, 
2.158541302, 0.891793295, 1.725196538, 1.141727408, 1.291906705, 
2.391879296, 1.475077386, 1.102099018, 1.208499439, 1.608445841, 
1.275157173, 1.475068786, 1.225057273, 1.29179213, 1.375061518, 
1.62511187, 1.458515113, 1.175086097, 1.325173291, 1.141661382, 
1.541854966, 0.891640437, 1.708388748, 2.508667999, 1.791765498, 
1.208331599, 1.758546351, 1.325188826, 1.275036217, 1.475070173, 
2.008490728, 1.591703522, 1.101920637, 1.341740835, 1.491791409, 
1.541778953, 1.391753069, 1.541872166, 1.102017734, 1.258391273, 
0.974974463, 0.90828122, 1.291834021, 1.425102049, 2.308734192, 
1.508330934, 1.158520772, 1.641787886, 0.724940479, 2.008608631, 
1.641750434, 0.708203154, 1.758491421, 1.658470282, 0.691591222, 
1.341717254, 1.608539054, 1.458390551, 2.325271775, 2.241825948, 
1.791821259, 1.891815766, 1.208526903, 1.325015161, 0.758281414, 
1.10965261976, 1.37513309242, 1.22519903524, 1.30854166216, 1.10197473366, 
1.15839843002, 1.20852218725, 1.19183313276, 1.10203687582, 1.30849283617, 
1.19171578394, 0.958308434856, 1.42508124255, 1.10204575328, 
0.908274006988, 1.12500395324, 1.40856585321, 1.1019153657, 0.958443538575, 
0.941628812658, 1.47504576049, 0.924951964663, 1.1019153657, 
1.10196752073, 1.54169378451, 1.22501177649, 1.10191869475, 0.90829092963, 
0.908266239217, 0.958333402688, 1.45836142215, 0.85834499886, 
1.10202744353, 0.958313705843, 0.908268736001, 0.808449281176, 
1.10205435331, 1.10191786249, 0.79179351713, 0.858266211475, 
1.10196668847, 1.42508151998, 1.1249706628, 1.72516352544, 1.15850995301, 
0.974938121387, 1.29183679471, 1.191713842, 0.808320835546, 1.1916525321, 
0.808365500225, 0.808249815932, 1.22504423468, 1.30837049379, 
0.741602346754, 1.12511603107, 1.42505932635, 0.974968360207, 
1.22501649264, 1.275043985, 0.94168374189, 1.10199997892, 1.49183746052, 
1.30836716475, 1.39183823729, 1.30836938411, 2.07520588753, 0.958485983891, 
1.65851910788, 0.924998848706, 1.72524425476, 1.10198028207, 
0.94175892281, 1.10193367545, 1.10194754647, 1.10203992745, 1.10204769522, 
1.22500012484, 1.10193728191, 0.891663462462, 0.925117029782, 
1.10200219828, 1.29175023955, 1.3083338743, 0.875121163346, 1.10196585621, 
1.77526425677, 1.2251629706, 0.891650423704, 1.10204408875, 1.10197695303, 
1.32506981284, 1.10202855321, 1.10197279172, 1.4085669629, 1.15834682983, 
1.52508545934, 0.791753568597, 0.908250148836, 1.40841188491, 
1.40849982717, 0.975095696156, 1.10194144322, 1.20839290936, 
1.52507602705, 1.10189705596, 0.891815488823, 1.10202994032, 
0.841608228066, 1.37504098886, 1.49169708581, 1.10196890783, 
1.50853206341, 0.924902583838, 0.891599100936, 1.10198915952, 
0.874946388514, 0.758285575417, 1.45891598546, 1.22515409314, 
1.82517939388, 1.5250998852, 1.4585664358, 1.10193228835, 1.10204436617, 
1.30839546162, 0.924993577719, 1.17497485184, 1.12509245034, 
1.10189400434, 1.14180120167, 1.10199248857, 0.908294258675, 
1.15838012028), Group = c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 
2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 
1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 
2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 
1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 
2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L)), row.names = c(NA, 
200L), class = "data.frame")
#There clearly is more than 1 value per group per participant.

groups <- aggregate(
  Group ~ participant,
  dfn,
  function(x) identical(sort(unique(x)), unique(dfn$Group))
)

compliant_participants <- groups[which(groups$Group),][["participant"]]
data_cleaned <- dfn[dfn$participant %in% compliant_participants,]
#The code falsely states that these participants are not compliant.

dfn我找到了一个解决方案：

替换

function(x) identical(sort(unique(x)), unique(dfn$Group))

借

这把戏是为我做的！请告诉我，如果我有，我不知怎么搞砸了：D
你能分享你期望获得的最终数据帧吗？最终数据帧应该与当前数据帧完全相同。关键是它没有，因为这些值被错误地删除了。但我明白你的意思，我将添加一个代码正常工作的示例。完成！我添加了一个数据框，代码准确地指出，所有参与者在每个条件下至少有一次试验。