我正在尝试打印与III型平方和结果的先验对比。 （请不要谈论第一类和第三类。这不是我的问题所在。）我可以使用func keyboardDidShow(notification: NSNotification) {
if let keyboardSize = (notification.userInfo?[UIKeyboardFrameBeginUserInfoKey] as? NSValue)?.CGRectValue() {
self.replaceKeyboardInputAccessoryView()
}
}
打印对比，但是使用I型SS 。当我使用summary.aov()中的Anova()函数获取III型SS时，它不会打印对比度。我也尝试将library(car)与drop1()模型一起使用，但这只会打印与lm()相同的结果（没有对比）。
请告知打印III型SS对比结果的方法。一个例子如下。
示例数据：
Anova()代码：
DF <- structure(list(Code = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L,
9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L), .Label = c("A",
"B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L"), class =
"factor"), GzrTreat = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), contrasts = structure(c(1,
-2, 1, 1, 0, -1), .Dim = c(3L, 2L), .Dimnames = list(c("I",
"N", "R"), NULL)), .Label = c("I", "N", "R"), class = "factor"),
BugTreat = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label =
c("Immigration", "Initial", "None"), class = "factor"), TempTreat =
structure(c(2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L), .Label = c("Not Warm", "Warmed"), class =
"factor"), ShadeTreat = structure(c(2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Light",
"Shaded"), class = "factor"), EpiChla = c(0.268482353, 0.423119608,
0.579507843, 0.738839216, 0.727856863, 0.523960784, 0.405801961,
0.335964706, 0.584441176, 0.557543137, 0.436456863, 0.563909804,
0.432398039, 0.344956863, 0.340309804, 0.992884314, 0.938390196,
0.663270588, 0.239833333, 0.62875098, 0.466011765, 0.536182353,
0.340309804, 0.721172549, 0.752082353, 0.269372549, 0.198180392,
1.298882353, 0.298354902, 0.913139216, 0.846129412, 0.922317647,
0.727033333, 1.187662745, 0.35622549, 0.073547059), log_EpiChla =
c(0.10328443, 0.153241402, 0.198521787, 0.240259426, 0.237507762,
0.182973791, 0.147924145, 0.125794985, 0.19987612, 0.192440084,
0.157292589, 0.194211702, 0.156063718, 0.128708355, 0.127205194,
0.299482089, 0.287441205, 0.220962908, 0.093363308, 0.21185469,
0.166137456, 0.186442772, 0.127205194, 0.235824411, 0.243554515,
0.103589102, 0.078522208, 0.361516746, 0.113393422, 0.281746574,
0.266262141, 0.283825153, 0.23730072, 0.339980371, 0.132331903,
0.030821087), MeanZGrowthAFDM_g = c(0.00665, 0.003966667, 0.004466667,
0.01705, 0.0139, 0.0129, 0.0081, 0.003833333, 0.00575, 0.011266667,
0.0103, 0.009, 0.0052, 0.00595, 0.0105, 0.0091, 0.00905, 0.0045, 0.0031,
0.006466667, 0.0053, 0.009766667, 0.0181, 0.00725, 0, 0.0012, 5e-04,
0.0076, 0.00615, 0.0814, NA, 0.0038, 0.00165, 0.0046, 0, 0.0015)),
.Names = c("Code", "GzrTreat", "BugTreat", "TempTreat", "ShadeTreat",
"EpiChla", "log_EpiChla", "MeanZGrowthAFDM_g"), class = "data.frame",
row.names = c(NA, -36L))