Question

我正在尝试执行包含两个因素的嵌套ANOVA 基本上，我有一个时间变量，每周都会测量一年。我想探讨季节和月份之间的差异，因此我在四个季节（seasons(months)=Winter(Jan, Feb, March), Spring(April, May, June), Summer(July, Sept), Autumn(Oct, Nov, Dec)）分配了三个不同的月份，导致嵌套的不平衡设计。

>modello<-lm(formula=y~season+season:month)
> anova(modello)

Analysis of Variance Table

Response: y
              Df Sum Sq Mean Sq F value    Pr(>F)    
season         3 178811   59604 144.216 < 2.2e-16 ***
season:month   7  41335    5905  14.287 < 2.2e-16 ***
Residuals    493 203754     413                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

然而，季节的df：月似乎不正确：嵌套ANOVA的df公式是A（B-1），在我的情况下是4（11-1）。我还进行了Tukey测试，但大部分结果都是NA：

$season
                   diff        lwr        upr p adj
Spring-Autumn  32.93056  26.453002  39.408109 0e+00
Summer-Autumn  15.14239   8.303663  21.981119 1e-07
Winter-Autumn -16.66300 -23.360587  -9.965413 0e+00
Summer-Spring -17.78816 -24.342077 -11.234252 0e+00
Winter-Spring -49.59356 -56.000055 -43.187056 0e+00
Winter-Summer -31.80539 -38.576856 -25.033926 0e+00

$`season:month`
                                         diff        lwr         upr     p adj
Spring:April-Autumn:April                  NA         NA          NA        NA
Summer:April-Autumn:April                  NA         NA          NA        NA
Winter:April-Autumn:April                  NA         NA          NA        NA
Autumn:December-Autumn:April               NA         NA          NA        NA

...

哪个是正确的程序？提前感谢您的帮助

恩尼奥

带有时间数据的嵌套ANOVA

0 个答案: