我建立了一个简单的线性回归模型,以“分数”作为因变量,“活动”作为独立变量。'Activity' 有 5 个级别:'listen'(参考级别)、'read1'、'read2'、'watch1'、'watch2'。
Call:
lm(formula = Score ~ Activity)
Residuals:
Min 1Q Median 3Q Max
-22.6154 -8.6154 -0.6154 7.1346 31.3846
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 41.615 2.553 16.302 <2e-16 ***
Activityread1 6.385 7.937 0.804 0.4254
Activityread2 20.885 9.552 2.186 0.0340 *
Activitywatch1 3.885 4.315 0.900 0.3728
Activitywatch2 -11.415 6.357 -1.796 0.0792 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 13.02 on 45 degrees of freedom
Multiple R-squared: 0.1901, Adjusted R-squared: 0.1181
F-statistic: 2.64 on 4 and 45 DF, p-value: 0.04594
为了获得所有成对比较,我执行了 TukeyHSD 测试,我很难解释其输出。虽然模型的输出显示我们唯一的显着效果是由于“listen”和“read2”之间的对比,但 TukeyHSD 结果表明,“watch2”和“read2”之间存在唯一的显着对比。这是什么意思?
> TukeyHSD(aov(mod4), "Activity")
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = mod4)
$Activity
diff lwr upr p adj
read1-listen 6.384615 -16.168371 28.937602 0.9279144
read2-listen 20.884615 -6.256626 48.025857 0.2034549
watch1-listen 3.884615 -8.376548 16.145779 0.8952957
watch2-listen -11.415385 -29.477206 6.646437 0.3885969
read2-read1 14.500000 -19.264610 48.264610 0.7397464
watch1-read1 -2.500000 -26.031639 21.031639 0.9981234
watch2-read1 -17.800000 -44.811688 9.211688 0.3466391
watch1-read2 -17.000000 -44.959754 10.959754 0.4278714
watch2-read2 -32.300000 -63.245777 -1.354223 0.0368820
watch2-watch1 -15.300000 -34.569930 3.969930 0.1783961