Shulou(Shulou.com)06/01 Report--

In this issue, Xiaobian will bring you about the multiple comparisons of R language. The article is rich in content and analyzed and described from a professional perspective. After reading this article, I hope you can gain something.

The F-test of ANOVA mentioned above can tell that five treatments are significantly different, but it does not know which treatment is different from others. Multiple comparisons can solve this problem. The TukeyHSD () function provides pairwise comparisons of differences in the means of groups. However, TukeyHSD () function is incompatible with HH package. When calling TukeyHSD () function, delete HH package from search path first, command: detach("package::HH"), otherwise TukeyHSD () function will be invalid.

TukeyHSD pairwise group comparisons:

> TukeyHSD(fit)

Tukey multiple comparisons of means

95% family-wise confidence level

Fit: aov(formula = response ~ trt)

$trt

diff lwr upr p adj

2times-1time 3.44300 -0.6582817 7.544282 0.1380949

4times-1time 6.59281 2.4915283 10.694092 0.0003542

drugD-1time 9.57920 5.4779183 13.680482 0.0000003

drugE-1time 15.16555 11.0642683 19.266832 0.0000000

4times-2times 3.14981 -0.9514717 7.251092 0.2050382

drugD-2times 6.13620 2.0349183 10.237482 0.0009611

drugE-2times 11.72255 7.6212683 15.823832 0.0000000

drugD-4times 2.98639 -1.1148917 7.087672 0.2512446

drugE-4times 8.57274 4.4714583 12.674022 0.0000037

drugE-drugD 5.58635 1.4850683 9.687632 0.0030633

> par(las=2)

> par(mar=c(5,8,4,2))

> plot(TukeyHSD(fit))

The results showed that the mean difference between 1times and 2times was not significant (p=0.138), and the difference between 1times and 4times was very significant (p

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