我有一个清单清单。我希望创建两个数据框。第一个变量将包含所有3个变量的ANOVA.test和Wald.test的结果（两者都具有相同的维，因此它们具有行绑定）。第二个DF将包含所有3个变量的r_varT的结果。
我完全不确定如何执行此操作，将不胜感激。
这是我的清单：
list(list(ex.f1np = structure(list(RTE = structure(list(RankMeans = c(46.5,
36.1666666666667, 30.6666666666667, 37.0833333333333, 34.875,
33.7083333333333), Nobs = c(12, 12, 12, 12, 12, 12), RTE = c(0.638888888888889,
0.49537037037037, 0.418981481481482, 0.508101851851852, 0.477430555555556,
0.461226851851852)), class = "data.frame", row.names = c("T1",
"T2", "T3", "T4", "T5", "T6")), Wald.test = structure(list(Statistic = 19.7348444620142,
df = 5, `p-value` = 0.00140128556409661), class = "data.frame", row.names = "T"),
Hotelling.test = structure(list(Statistic = 2.51170747698362,
df1 = 5, df2 = 7, `p-value` = 0.130852715747306), class = "data.frame", row.names = "T"),
ANOVA.test = structure(list(Statistic = 1.86005194215863,
df = 2.85939233428426, `p-value` = 0.136888434365296), class = "data.frame", row.names = "T"),
two.sample.test = NULL, two.sample.BF.test = NULL, pattern.test = NULL,
covariance = NULL, model.name = "LD F1 Model", Conf.Int = structure(list(
Group = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "Group1", class = "factor"),
Time = 1:6, Nobs = c(12, 12, 12, 12, 12, 12), RankMeans = c(46.5,
36.1667, 30.6667, 37.0833, 34.875, 33.7083), RTE = c(0.6389,
0.4954, 0.419, 0.5081, 0.4774, 0.4612), Bias = c(0.0013,
-8e-04, 4e-04, -1e-04, 8e-04, -0.0015), Variance = c(0.0351,
0.0262, 0.0219, 0.0277, 0.0384, 0.038), Lower = c(0.5252,
0.4055, 0.3396, 0.4151, 0.3707, 0.356), Upper = c(0.7333,
0.5857, 0.505, 0.6003, 0.5872, 0.5716)), class = "data.frame", row.names = c(NA,
-6L)), input = list(formula = "A ~ T", data = structure(list(
Patient = c("TLA001", "TLA001", "TLA001", "TLA001", "TLA001",
"TLA001", "TLA003", "TLA003", "TLA003", "TLA003", "TLA003",
"TLA003", "TLA004", "TLA004", "TLA004", "TLA004", "TLA004",
"TLA004", "TLA005", "TLA005", "TLA005", "TLA005", "TLA005",
"TLA005", "TLA006", "TLA006", "TLA006", "TLA006", "TLA006",
"TLA006", "TLA008", "TLA008", "TLA008", "TLA008", "TLA008",
"TLA008", "TLA009", "TLA009", "TLA009", "TLA009", "TLA009",
"TLA009", "TLA010", "TLA010", "TLA010", "TLA010", "TLA010",
"TLA010", "TLA011", "TLA011", "TLA011", "TLA011", "TLA011",
"TLA011", "TLA012", "TLA012", "TLA012", "TLA012", "TLA012",
"TLA012", "TLA013", "TLA013", "TLA013", "TLA013", "TLA013",
"TLA013", "TLA015", "TLA015", "TLA015", "TLA015", "TLA015",
"TLA015"), id = c(1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 11L,
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L,
13L, 13L, 13L, 13L, 13L, 13L, 15L, 15L, 15L, 15L, 15L,
15L), Night = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L,
6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L), .Label = c("TLA -3",
"TLA -2", "TLA -1", "TLA 1", "TLA 2", "TLA 3"), class = "factor"),
T = c(1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L,
5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L), A = c(0.1, 0, 0, 0, 0, 0, 0.3, 0, 0.4,
0.3, 0, 2.2, 1.1, 0.6, 2.1, 1.4, 1.7, 0.9, 0.3, 0.3,
0, 1, 0, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 0.2, 0.1, 0.1, 0.4,
0, 0.4, 0.1, 0, 0, 0, 0, 1.1, 0.8, 0, 0, 0.6, 0, 0, 0,
0, 0, 0, 0, 2, 0.9, 0.2, 0.4, 0.3, 1, 0, 0, 0, 0.3, 0.3,
0, 0.7, 0, 0, 0, 0, 0), B = c(5L, 7L, 12L, 5L, 5L, 4L,
4L, 1L, 2L, 3L, 0L, 1L, 17L, 5L, 2L, 16L, 20L, 14L, 21L,
36L, 15L, 17L, 18L, 9L, 1L, 2L, 1L, 0L, 1L, 0L, 2L, 12L,
5L, 1L, 1L, 0L, 3L, 0L, 1L, 1L, 1L, 1L, 7L, 7L, 5L, 2L,
6L, 5L, 7L, 3L, 8L, 1L, 3L, 3L, 2L, 2L, 2L, 4L, 4L, 2L,
1L, 1L, 0L, 0L, 0L, 0L, 1L, 4L, 3L, 7L, 2L, 1L), C = c(0.5,
0.8, 1.4, 0.6, 0.5, 0.5, 0.5, 0.1, 0.9, 0.4, 0, 0.1,
2.1, 1, 0.3, 1.6, 2.1, 2, 2.4, 3.9, 2.4, 2.5, 2.3, 1.3,
0.9, 0.4, 0.2, 0, 0.4, 0, 0.3, 1.3, 0.7, 0.1, 0.1, 0,
0.4, 0, 0.2, 0.2, 0.1, 0.2, 1, 0.8, 0.6, 0.5, 0.9, 0.6,
0.9, 0.4, 0.9, 0.1, 0.4, 0.5, 0.3, 0.3, 0.5, 0.5, 0.5,
0.3, 0.1, 0.2, 0, 0, 0, 0, 0.4, 1, 0.5, 1.5, 0.5, 0.3
), D = c(1L, 0L, 1L, 0L, 1L, 0L, 2L, 0L, 1L, 2L, 2L,
15L, 9L, 7L, 15L, 10L, 21L, 6L, 3L, 4L, 0L, 10L, 0L,
3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 5L, 0L, 3L,
1L, 0L, 0L, 3L, 0L, 4L, 15L, 0L, 0L, 6L, 0L, 0L, 3L,
0L, 5L, 0L, 2L, 15L, 10L, 1L, 5L, 5L, 7L, 0L, 0L, 0L,
3L, 1L, 0L, 2L, 2L, 0L, 1L, 0L, 0L), E = c(0.1, 0, 0.1,
0, 0.1, 0, 0.3, 0, 0.4, 0.3, 0.3, 2.2, 1.1, 1.3, 2.1,
1, 2.2, 0.9, 0.3, 0.4, 0, 1.5, 0, 0.4, 0, 0, 0, 0, 0,
0, 0, 0.2, 0, 0, 0.6, 0, 0.4, 0.1, 0, 0, 0.4, 0, 0.6,
1.7, 0, 0, 0.9, 0, 0, 0.4, 0, 0.7, 0, 0.3, 2.3, 1.3,
0.2, 0.6, 0.7, 1, 0, 0, 0, 0.5, 0.3, 0, 0.7, 0.5, 0,
0.2, 0, 0)), row.names = c(NA, -72L), spec = structure(list(
cols = list(Patient = structure(list(), class = c("collector_character",
"collector")), id = structure(list(), class = c("collector_integer",
"collector")), Night = structure(list(), class = c("collector_character",
"collector")), T = structure(list(), class = c("collector_integer",
"collector")), A = structure(list(), class = c("collector_double",
"collector")), B = structure(list(), class = c("collector_integer",
"collector")), C = structure(list(), class = c("collector_double",
"collector")), D = structure(list(), class = c("collector_integer",
"collector")), E = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector"))), class = "col_spec"), class = "data.frame"),
subject = "id", description = FALSE, time1.order = NULL,
time2.order = NULL, group1.order = NULL, group2.order = NULL,
plot.CI = FALSE, alpha = 0.05, show.covariance = FALSE,
order.warning = TRUE)), class = "nparLD"), r_varT = structure(c(7.20920785375762,
1, 0.00725304991088717, 7.20920785375763, 1, 0.00725304991088716,
7.34628975265018, 1, 0.00672013023266443, 7.34628975265018, 1,
0.00672013023266444, 1.9953488372093, 1, 0.157782733274174, 1.9953488372093,
1, 0.157782733274174, 3.27830985915493, 1, 0.0702011880921252,
3.27830985915493, 0.999999999999999, 0.0702011880921251, 4.2753036437247,
1, 0.0386700541436081, 4.2753036437247, 1, 0.0386700541436082
), .Dim = c(3L, 10L), .Dimnames = list(c("varS", "varDF", "varP"
), c("AT12", "WT12", "AT13", "WT13", "AT14", "WT14", "AT15",
"WT15", "AT16", "WT16")))), list(ex.f1np = structure(list(RTE = structure(list(
RankMeans = c(41.5416666666667, 40.1666666666667, 38.125,
34.6666666666667, 34.875, 29.625), Nobs = c(12, 12, 12, 12,
12, 12), RTE = c(0.570023148148148, 0.550925925925926, 0.522569444444444,
0.474537037037037, 0.477430555555556, 0.404513888888889)), class = "data.frame", row.names = c("T1",
"T2", "T3", "T4", "T5", "T6")), Wald.test = structure(list(Statistic = 94.686438839942,
df = 5, `p-value` = 6.95084205022086e-19), class = "data.frame", row.names = "T"),
Hotelling.test = structure(list(Statistic = 12.0510013069017,
df1 = 5, df2 = 7, `p-value` = 0.00248759860990302), class = "data.frame", row.names = "T"),
ANOVA.test = structure(list(Statistic = 1.53166545929456,
df = 2.96689828062647, `p-value` = 0.204426890714885), class = "data.frame", row.names = "T"),
two.sample.test = NULL, two.sample.BF.test = NULL, pattern.test = NULL,
covariance = NULL, model.name = "LD F1 Model", Conf.Int = structure(list(
Group = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "Group1", class = "factor"),
Time = 1:6, Nobs = c(12, 12, 12, 12, 12, 12), RankMeans = c(41.5417,
40.1667, 38.125, 34.6667, 34.875, 29.625), RTE = c(0.57,
0.5509, 0.5226, 0.4745, 0.4774, 0.4045), Bias = c(0.0075,
0.0055, -8e-04, -0.0021, 0.0021, -0.0122), Variance = c(0.0218,
0.0294, 0.0336, 0.0354, 0.018, 0.0145), Lower = c(0.4847,
0.4528, 0.4196, 0.372, 0.4031, 0.3397), Upper = c(0.6497,
0.6436, 0.6228, 0.5803, 0.5533, 0.4747)), class = "data.frame", row.names = c(NA,
-6L)), input = list(formula = "B ~ T", data = structure(list(
Patient = c("TLA001", "TLA001", "TLA001", "TLA001", "TLA001",
"TLA001", "TLA003", "TLA003", "TLA003", "TLA003", "TLA003",
"TLA003", "TLA004", "TLA004", "TLA004", "TLA004", "TLA004",
"TLA004", "TLA005", "TLA005", "TLA005", "TLA005", "TLA005",
"TLA005", "TLA006", "TLA006", "TLA006", "TLA006", "TLA006",
"TLA006", "TLA008", "TLA008", "TLA008", "TLA008", "TLA008",
"TLA008", "TLA009", "TLA009", "TLA009", "TLA009", "TLA009",
"TLA009", "TLA010", "TLA010", "TLA010", "TLA010", "TLA010",
"TLA010", "TLA011", "TLA011", "TLA011", "TLA011", "TLA011",
"TLA011", "TLA012", "TLA012", "TLA012", "TLA012", "TLA012",
"TLA012", "TLA013", "TLA013", "TLA013", "TLA013", "TLA013",
"TLA013", "TLA015", "TLA015", "TLA015", "TLA015", "TLA015",
"TLA015"), id = c(1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 11L,
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L,
13L, 13L, 13L, 13L, 13L, 13L, 15L, 15L, 15L, 15L, 15L,
15L), Night = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L,
6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L), .Label = c("TLA -3",
"TLA -2", "TLA -1", "TLA 1", "TLA 2", "TLA 3"), class = "factor"),
T = c(1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L,
5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L), A = c(0.1, 0, 0, 0, 0, 0, 0.3, 0, 0.4,
0.3, 0, 2.2, 1.1, 0.6, 2.1, 1.4, 1.7, 0.9, 0.3, 0.3,
0, 1, 0, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 0.2, 0.1, 0.1, 0.4,
0, 0.4, 0.1, 0, 0, 0, 0, 1.1, 0.8, 0, 0, 0.6, 0, 0, 0,
0, 0, 0, 0, 2, 0.9, 0.2, 0.4, 0.3, 1, 0, 0, 0, 0.3, 0.3,
0, 0.7, 0, 0, 0, 0, 0), B = c(5L, 7L, 12L, 5L, 5L, 4L,
4L, 1L, 2L, 3L, 0L, 1L, 17L, 5L, 2L, 16L, 20L, 14L, 21L,
36L, 15L, 17L, 18L, 9L, 1L, 2L, 1L, 0L, 1L, 0L, 2L, 12L,
5L, 1L, 1L, 0L, 3L, 0L, 1L, 1L, 1L, 1L, 7L, 7L, 5L, 2L,
6L, 5L, 7L, 3L, 8L, 1L, 3L, 3L, 2L, 2L, 2L, 4L, 4L, 2L,
1L, 1L, 0L, 0L, 0L, 0L, 1L, 4L, 3L, 7L, 2L, 1L), C = c(0.5,
0.8, 1.4, 0.6, 0.5, 0.5, 0.5, 0.1, 0.9, 0.4, 0, 0.1,
2.1, 1, 0.3, 1.6, 2.1, 2, 2.4, 3.9, 2.4, 2.5, 2.3, 1.3,
0.9, 0.4, 0.2, 0, 0.4, 0, 0.3, 1.3, 0.7, 0.1, 0.1, 0,
0.4, 0, 0.2, 0.2, 0.1, 0.2, 1, 0.8, 0.6, 0.5, 0.9, 0.6,
0.9, 0.4, 0.9, 0.1, 0.4, 0.5, 0.3, 0.3, 0.5, 0.5, 0.5,
0.3, 0.1, 0.2, 0, 0, 0, 0, 0.4, 1, 0.5, 1.5, 0.5, 0.3
), D = c(1L, 0L, 1L, 0L, 1L, 0L, 2L, 0L, 1L, 2L, 2L,
15L, 9L, 7L, 15L, 10L, 21L, 6L, 3L, 4L, 0L, 10L, 0L,
3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 5L, 0L, 3L,
1L, 0L, 0L, 3L, 0L, 4L, 15L, 0L, 0L, 6L, 0L, 0L, 3L,
0L, 5L, 0L, 2L, 15L, 10L, 1L, 5L, 5L, 7L, 0L, 0L, 0L,
3L, 1L, 0L, 2L, 2L, 0L, 1L, 0L, 0L), E = c(0.1, 0, 0.1,
0, 0.1, 0, 0.3, 0, 0.4, 0.3, 0.3, 2.2, 1.1, 1.3, 2.1,
1, 2.2, 0.9, 0.3, 0.4, 0, 1.5, 0, 0.4, 0, 0, 0, 0, 0,
0, 0, 0.2, 0, 0, 0.6, 0, 0.4, 0.1, 0, 0, 0.4, 0, 0.6,
1.7, 0, 0, 0.9, 0, 0, 0.4, 0, 0.7, 0, 0.3, 2.3, 1.3,
0.2, 0.6, 0.7, 1, 0, 0, 0, 0.5, 0.3, 0, 0.7, 0.5, 0,
0.2, 0, 0)), row.names = c(NA, -72L), spec = structure(list(
cols = list(Patient = structure(list(), class = c("collector_character",
"collector")), id = structure(list(), class = c("collector_integer",
"collector")), Night = structure(list(), class = c("collector_character",
"collector")), T = structure(list(), class = c("collector_integer",
"collector")), A = structure(list(), class = c("collector_double",
"collector")), B = structure(list(), class = c("collector_integer",
"collector")), C = structure(list(), class = c("collector_double",
"collector")), D = structure(list(), class = c("collector_integer",
"collector")), E = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector"))), class = "col_spec"), class = "data.frame"),
subject = "id", description = FALSE, time1.order = NULL,
time2.order = NULL, group1.order = NULL, group2.order = NULL,
plot.CI = FALSE, alpha = 0.05, show.covariance = FALSE,
order.warning = TRUE)), class = "nparLD"), r_varT = structure(c(0.0145310435931308,
1, 0.904051610218717, 0.0145310435931308, 1, 0.904051610218716,
0.346634346447883, 1, 0.556024556253589, 0.346634346447883, 1,
0.556024556253589, 1.52530915086562, 1, 0.216817825047153, 1.52530915086562,
1, 0.216817825047153, 2.48960739030023, 1, 0.114600309334707,
2.48960739030023, 1, 0.114600309334707, 18.6079295154185, 1,
1.60551351695372e-05, 18.6079295154185, 1, 1.60551351695373e-05
), .Dim = c(3L, 10L), .Dimnames = list(c("varS", "varDF", "varP"
), c("AT12", "WT12", "AT13", "WT13", "AT14", "WT14", "AT15",
"WT15", "AT16", "WT16")))), list(ex.f1np = structure(list(RTE = structure(list(
RankMeans = c(42.1666666666667, 39.4166666666667, 40.25,
34.25, 33.875, 29.0416666666667), Nobs = c(12, 12, 12, 12,
12, 12), RTE = c(0.578703703703704, 0.540509259259259, 0.552083333333333,
0.46875, 0.463541666666667, 0.396412037037037)), class = "data.frame", row.names = c("T1",
"T2", "T3", "T4", "T5", "T6")), Wald.test = structure(list(Statistic = 13.3608330377708,
df = 5, `p-value` = 0.0202221016002875), class = "data.frame", row.names = "T"),
Hotelling.test = structure(list(Statistic = 1.70046965935264,
df1 = 5, df2 = 7, `p-value` = 0.252317791943035), class = "data.frame", row.names = "T"),
ANOVA.test = structure(list(Statistic = 1.64153150442253,
df = 3.44705833042218, `p-value` = 0.169822389412102), class = "data.frame", row.names = "T"),
two.sample.test = NULL, two.sample.BF.test = NULL, pattern.test = NULL,
covariance = NULL, model.name = "LD F1 Model", Conf.Int = structure(list(
Group = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "Group1", class = "factor"),
Time = 1:6, Nobs = c(12, 12, 12, 12, 12, 12), RankMeans = c(42.1667,
39.4167, 40.25, 34.25, 33.875, 29.0417), RTE = c(0.5787,
0.5405, 0.5521, 0.4688, 0.4635, 0.3964), Bias = c(0.0061,
0.002, 0.0022, -3e-04, -0.0017, -0.0083), Variance = c(0.0318,
0.0322, 0.0585, 0.0335, 0.0191, 0.0185), Lower = c(0.4751,
0.4385, 0.4145, 0.3691, 0.3876, 0.3239), Upper = c(0.6732,
0.6378, 0.679, 0.5721, 0.5421, 0.4762)), class = "data.frame", row.names = c(NA,
-6L)), input = list(formula = "C ~ T", data = structure(list(
Patient = c("TLA001", "TLA001", "TLA001", "TLA001", "TLA001",
"TLA001", "TLA003", "TLA003", "TLA003", "TLA003", "TLA003",
"TLA003", "TLA004", "TLA004", "TLA004", "TLA004", "TLA004",
"TLA004", "TLA005", "TLA005", "TLA005", "TLA005", "TLA005",
"TLA005", "TLA006", "TLA006", "TLA006", "TLA006", "TLA006",
"TLA006", "TLA008", "TLA008", "TLA008", "TLA008", "TLA008",
"TLA008", "TLA009", "TLA009", "TLA009", "TLA009", "TLA009",
"TLA009", "TLA010", "TLA010", "TLA010", "TLA010", "TLA010",
"TLA010", "TLA011", "TLA011", "TLA011", "TLA011", "TLA011",
"TLA011", "TLA012", "TLA012", "TLA012", "TLA012", "TLA012",
"TLA012", "TLA013", "TLA013", "TLA013", "TLA013", "TLA013",
"TLA013", "TLA015", "TLA015", "TLA015", "TLA015", "TLA015",
"TLA015"), id = c(1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 11L,
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L,
13L, 13L, 13L, 13L, 13L, 13L, 15L, 15L, 15L, 15L, 15L,
15L), Night = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L,
6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L,
2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L,
4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L), .Label = c("TLA -3",
"TLA -2", "TLA -1", "TLA 1", "TLA 2", "TLA 3"), class = "factor"),
T = c(1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L,
5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L,
3L, 4L, 5L, 6L), A = c(0.1, 0, 0, 0, 0, 0, 0.3, 0, 0.4,
0.3, 0, 2.2, 1.1, 0.6, 2.1, 1.4, 1.7, 0.9, 0.3, 0.3,
0, 1, 0, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 0.2, 0.1, 0.1, 0.4,
0, 0.4, 0.1, 0, 0, 0, 0, 1.1, 0.8, 0, 0, 0.6, 0, 0, 0,
0, 0, 0, 0, 2, 0.9, 0.2, 0.4, 0.3, 1, 0, 0, 0, 0.3, 0.3,
0, 0.7, 0, 0, 0, 0, 0), B = c(5L, 7L, 12L, 5L, 5L, 4L,
4L, 1L, 2L, 3L, 0L, 1L, 17L, 5L, 2L, 16L, 20L, 14L, 21L,
36L, 15L, 17L, 18L, 9L, 1L, 2L, 1L, 0L, 1L, 0L, 2L, 12L,
5L, 1L, 1L, 0L, 3L, 0L, 1L, 1L, 1L, 1L, 7L, 7L, 5L, 2L,
6L, 5L, 7L, 3L, 8L, 1L, 3L, 3L, 2L, 2L, 2L, 4L, 4L, 2L,
1L, 1L, 0L, 0L, 0L, 0L, 1L, 4L, 3L, 7L, 2L, 1L), C = c(0.5,
0.8, 1.4, 0.6, 0.5, 0.5, 0.5, 0.1, 0.9, 0.4, 0, 0.1,
2.1, 1, 0.3, 1.6, 2.1, 2, 2.4, 3.9, 2.4, 2.5, 2.3, 1.3,
0.9, 0.4, 0.2, 0, 0.4, 0, 0.3, 1.3, 0.7, 0.1, 0.1, 0,
0.4, 0, 0.2, 0.2, 0.1, 0.2, 1, 0.8, 0.6, 0.5, 0.9, 0.6,
0.9, 0.4, 0.9, 0.1, 0.4, 0.5, 0.3, 0.3, 0.5, 0.5, 0.5,
0.3, 0.1, 0.2, 0, 0, 0, 0, 0.4, 1, 0.5, 1.5, 0.5, 0.3
), D = c(1L, 0L, 1L, 0L, 1L, 0L, 2L, 0L, 1L, 2L, 2L,
15L, 9L, 7L, 15L, 10L, 21L, 6L, 3L, 4L, 0L, 10L, 0L,
3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 5L, 0L, 3L,
1L, 0L, 0L, 3L, 0L, 4L, 15L, 0L, 0L, 6L, 0L, 0L, 3L,
0L, 5L, 0L, 2L, 15L, 10L, 1L, 5L, 5L, 7L, 0L, 0L, 0L,
3L, 1L, 0L, 2L, 2L, 0L, 1L, 0L, 0L), E = c(0.1, 0, 0.1,
0, 0.1, 0, 0.3, 0, 0.4, 0.3, 0.3, 2.2, 1.1, 1.3, 2.1,
1, 2.2, 0.9, 0.3, 0.4, 0, 1.5, 0, 0.4, 0, 0, 0, 0, 0,
0, 0, 0.2, 0, 0, 0.6, 0, 0.4, 0.1, 0, 0, 0.4, 0, 0.6,
1.7, 0, 0, 0.9, 0, 0, 0.4, 0, 0.7, 0, 0.3, 2.3, 1.3,
0.2, 0.6, 0.7, 1, 0, 0, 0, 0.5, 0.3, 0, 0.7, 0.5, 0,
0.2, 0, 0)), row.names = c(NA, -72L), spec = structure(list(
cols = list(Patient = structure(list(), class = c("collector_character",
"collector")), id = structure(list(), class = c("collector_integer",
"collector")), Night = structure(list(), class = c("collector_character",
"collector")), T = structure(list(), class = c("collector_integer",
"collector")), A = structure(list(), class = c("collector_double",
"collector")), B = structure(list(), class = c("collector_integer",
"collector")), C = structure(list(), class = c("collector_double",
"collector")), D = structure(list(), class = c("collector_integer",
"collector")), E = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector"))), class = "col_spec"), class = "data.frame"),
subject = "id", description = FALSE, time1.order = NULL,
time2.order = NULL, group1.order = NULL, group2.order = NULL,
plot.CI = FALSE, alpha = 0.05, show.covariance = FALSE,
order.warning = TRUE)), class = "nparLD"), r_varT = structure(c(0.181261064959826,
1, 0.670291733702588, 0.181261064959826, 1, 0.670291733702588,
0.0985074626865672, 1, 0.753628142361081, 0.0985074626865672,
1, 0.753628142361082, 1.4114627887083, 1, 0.234813713730428,
1.4114627887083, 1, 0.234813713730428, 2.55399855037448, 1, 0.110015506496831,
2.55399855037448, 1, 0.110015506496831, 11.4150943396226, 1,
0.000728497975523072, 11.4150943396226, 1, 0.000728497975523073
), .Dim = c(3L, 10L), .Dimnames = list(c("varS", "varDF", "varP"
), c("AT12", "WT12", "AT13", "WT13", "AT14", "WT14", "AT15",
"WT15", "AT16", "WT16")))))```
答案 0 :(得分：1)
您可以尝试的第一部分
do.call(rbind,lapply(lst, function(x)
rbind(x$ex.f1np$Wald.test, x$ex.f1np$ANOVA.test)))
# Statistic df p-value
#T 19.7348 5.0000 1.4013e-03
#T1 1.8601 2.8594 1.3689e-01
#T2 94.6864 5.0000 6.9508e-19
#T11 1.5317 2.9669 2.0443e-01
#T3 13.3608 5.0000 2.0222e-02
#T12 1.6415 3.4471 1.6982e-01
第二个数据帧
do.call(rbind, lapply(lst, function(x) x$r_varT))
等效的purrr版本为
purrr::map_dfr(lst, ~ rbind(.$ex.f1np$Wald.test, .$ex.f1np$ANOVA.test))
purrr::map_dfr(lst, ~ .$r_varT %>% data.frame)