混合 ANOVA で実行している R コードの何が問題なのかを理解するのに苦労しています。イライラすることに、コンピューターごとに aov 関数の結果が異なります (1 つは Mac、もう 1 つは PC)。また、Mac で aov 関数を使用して取得した結果は、同じコンピューターで ezANOVA を使用して取得した結果とは大きく異なります。SPSS で同じ分析を実行し、ezANOVA と同じ結果を得たので、私の aov ラインに問題があるようです。ただし、前に述べたように、同じコードとデータ ファイルを使用しても、PC では異なる結果が得られます。私は問題が本当に単純なものであることに偏執的ですが、それを理解することができず、分析を完了するのを妨げています.
デフォルト設定を台無しにしてしまった可能性のあることはありますか? コンピューターを再起動しても、同じ結果が得られます。
> ex.data <- structure(list(RT = c(459.15, 506.75, 382.05, 395.75, 422.263157894737,
374, 433.75, 401.85, 573.8, 473.15, 335.35, 405.842105263158,
390.05, 354.35, 369.7, 650.421052631579, 400.8, 426.8, 477.6,
517.05, 451.3, 405.9, 380.15, 346, 595.8, 336, 451.5, 440.55,
718.3, 439.55, 423.05, 560, 669.333333333333, 525.578947368421,
358.75, 505.8, 426, 417.4, 361.65, 409.85, 486.631578947368,
540, 438, 357.2, 401.35, 407.45, 397.166666666667, 406.052631578947,
445.85, 467.6, 353.35, 366.3, 431.6, 326.6, 433.105263157895,
347.75, 512.105263157895, 443.85, 296.85, 408.058823529412, 364.3,
315.9, 341.5, 646.058823529412, 373.5, 414.45, 475.45, 489.45,
429.368421052632, 419.35, 370.2, 327.75, 569.85, 347, 415.35,
429.5, 738.15, 406.4, 400.3, 522.941176470588, 631.555555555556,
484.9, 355.684210526316, 465.9, 415.5, 445.631578947368, 400.555555555556,
387.4, 477.3, 503.95, 404, 394.5, 385.65, 383.55, 439.65, 371.421052631579),
TrialType = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("dtprb.con.neg", "dtprb.incon.neg"
), class = "factor"), subject = c(2L, 3L, 5L, 6L, 7L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 100L, 101L, 102L, 103L,
106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L, 116L, 118L,
119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L, 200L,
201L, 204L, 206L, 210L, 211L, 400L, 401L, 2L, 3L, 5L, 6L, 7L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 100L, 101L,
102L, 103L, 106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L,
116L, 118L, 119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L,
128L, 200L, 201L, 204L, 206L, 210L, 211L, 400L, 401L), condition = c("placebo",
"drug", "placebo", "drug", "placebo", "drug", "placebo", "drug",
"drug", "placebo", "drug", "drug", "placebo", "placebo", "drug",
"placebo", "placebo", "drug", "drug", "placebo", "drug", "placebo",
"drug", "drug", "drug", "placebo", "placebo", "drug", "placebo",
"drug", "drug", "drug", "placebo", "placebo", "placebo", "drug",
"drug", "placebo", "placebo", "drug", "placebo", "placebo", "placebo",
"placebo", "drug", "drug", "drug", "placebo", "placebo", "drug",
"placebo", "drug", "placebo", "drug", "placebo", "drug", "drug",
"placebo", "drug", "drug", "placebo", "placebo", "drug", "placebo",
"placebo", "drug", "drug", "placebo", "drug", "placebo", "drug",
"drug", "drug", "placebo", "placebo", "drug", "placebo", "drug",
"drug", "drug", "placebo", "placebo", "placebo", "drug", "drug",
"placebo", "placebo", "drug", "placebo", "placebo", "placebo",
"placebo", "drug", "drug", "drug", "placebo")), .Names = c("RT",
"TrialType", "subject", "condition"), row.names = c(NA, -96L), class = "data.frame")
> anova_ex.data <- aov(RT ~ TrialType*condition + Error(subject/TrialType) + condition, data=ex.data)
> summary(anova_ex.data)
Error: subject
Df Sum Sq Mean Sq
condition 1 3267 3267
Error: subject:TrialType
Df Sum Sq Mean Sq
TrialType 1 1738 1738
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
TrialType 1 6747 6747 0.883 0.350
condition 1 16743 16743 2.191 0.142
TrialType:condition 1 763 763 0.100 0.753
Residuals 90 687713 7641
> ezANOVA(data = ex.data, dv = .(RT), wid = .(subject), within = .(TrialType), between = .(condition), detailed = TRUE, type = 3)
Warning: Converting "subject" to factor for ANOVA.
Warning: Converting "condition" to factor for ANOVA.
$ANOVA
Effect DFn DFd SSn SSd F p p<.05 ges
1 (Intercept) 1 46 8620839.9719 678628.80 584.352798 8.648708e-28 * 0.925761817
2 condition 1 46 17592.2597 678628.80 1.192469 2.805185e-01 0.024815931
3 TrialType 1 46 6552.8332 12688.87 23.755499 1.340138e-05 * 0.009389755
4 condition:TrialType 1 46 887.0503 12688.87 3.215757 7.950840e-02 0.001281485
どんな助けでも大歓迎です!