Differences

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--- r:anova [2023/06/05 19:19] – [Post hoc test] hkimscil
+++ r:anova [2024/04/17 08:29] – [ANOVA in R: Output] hkimscil
@@ Line 42: / Line 42: @@
 var(comb3$values)
+# within part 구하기
+# 간단한 방법
+tapply(comb3$values, comb3$group, var)*15
+sse <- sum(tapply(comb3$values, comb3$group, var)*15)
+sse
+# 이해한 개념대로 얼른 구하기
 # A, B, C 평균
 m.a <- mean(A)
@@ Line 59: / Line 66: @@
 ss.within <- ss.a + ss.b + ss.c
-ss.within <- ss.within
+ss.within == sse # check both are the same
+# between part 구하기
 *((m.a-mean.tot)^2)
 *((m.b-mean.tot)^2)
@@ Line 274: / Line 283: @@
 [1] 56.7234
 >
+> # within part 구하기
+> # 간단한 방법
+> tapply(comb3$values, comb3$group, var)*15
+  a   b   c
+750 900
+> sse <- sum(tapply(comb3$values, comb3$group, var)*15)
+> sse
+[1] 2250
+>
+> # 이해한 개념대로 얼른 구하기
 > # A, B, C 평균
 > m.a <- mean(A)
@@ Line 291: / Line 310: @@
 >
 > ss.within <- ss.a + ss.b + ss.c
-> ss.within <- ss.within
+> ss.within == sse # check both are the same
+[1] TRUE
+>
 >
+> # between part 구하기
 > 16*((m.a-mean.tot)^2)
 [1] 144
@@ Line 350: / Line 372: @@
 ---
 Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+>
+>
+</code>
+<code>
 > # 위에서
 > # ssd라는 function을 만들면
@@ Line 356: / Line 383: @@
 +     var(x) * (length(x)-1) }
 > ss.a1 <- ssd(A)
-> ss.b2 <- ssd(B)
+> ss.b1 <- ssd(B)
 > ss.c1 <- ssd(C)
 >
@@ Line 365: / Line 392: @@
 > ss.c == ss.c1
 [1] TRUE
-> # 그러나 정확히 어떤 그룹에서 차이가 나는지는 판단해주지 않음
-> pairwise.t.test(comb3$values, comb3$group, p.adj = "none")
-	Pairwise comparisons using t tests with pooled SD
-data:  comb3$values and comb3$group
-  a      b
-b 0.4279 -
-c 0.0075 0.0516
-P value adjustment method: none
-> # OR
-> pairwise.t.test(comb3$values, comb3$group, p.adj = "bonf")
-	Pairwise comparisons using t tests with pooled SD
-data:  comb3$values and comb3$group
-  a     b
-b 1.000 -
-c 0.023 0.155
-P value adjustment method: bonferroni
-> pairwise.t.test(comb3$values, comb3$group, p.adj = "holm")
-	Pairwise comparisons using t tests with pooled SD
-data:  comb3$values and comb3$group
-  a     b
-b 0.428 -
-c 0.023 0.103
-P value adjustment method: holm
 >
-> # OR TukeyHSD(anova.output)
+</code>
-> TukeyHSD(a.res)
-  Tukey multiple comparisons of means
-% family-wise confidence level
-Fit: aov(formula = values ~ group, data = comb3)
+<code>
-$group
-    diff        lwr       upr     p adj
-b-a   -2  -8.059034  4.059034 0.7049466
-c-a   -7 -13.059034 -0.940966 0.0201250
-c-b   -5 -11.059034  1.059034 0.1238770
->
->
->
 </code>
 ====== Post hoc test ======
 [[:post hoc test]]