如何使用按栏组织的样本在R中执行单因素ANOVA? [英] How to perform single factor ANOVA in R with samples organized by column?
问题描述
我有一个数据集，其中样本按列分组.以下样本数据集与我的数据格式相似:
I have a data set where the samples are grouped by column. The following sample dataset is similar to my data's format:
a = c(1,3,4,6,8)
b = c(3,6,8,3,6)
c = c(2,1,4,3,6)
d = c(2,2,3,3,4)
mydata = data.frame(cbind(a,b,c,d))
当我使用上述数据集在Excel中执行单因素方差分析时，得到以下结果:
When I perform a single factor ANOVA in Excel using the above dataset, I get the following results:
我知道R中的典型格式如下:
I know a typical format in R is as follows:
group measurement
a 1
a 3
a 4
. .
. .
. .
d 4
在R中执行ANOVA的命令将使用aov(group~measurement, data = mydata). 如何用按列而不是按行组织的样本在R中执行单因素ANOVA?换句话说，如何使用R复制Excel结果?非常感谢您的帮助.
And the command to perform ANOVA in R would be to use aov(group~measurement, data = mydata). How do I perform single factor ANOVA in R with samples organized by column rather than by row? In other words, how do I duplicate the excel results using R? Many thanks for the help.
推荐答案
您将它们以长格式堆叠:
You stack them in the long format:
mdat <- stack(mydata)
mdat
values ind
1 1 a
2 3 a
3 4 a
4 6 a
5 8 a
6 3 b
7 6 b
snipped output
> aov( values ~ ind, mdat)
Call:
aov(formula = values ~ ind, data = mdat)
Terms:
ind Residuals
Sum of Squares 18.2 65.6
Deg. of Freedom 3 16
Residual standard error: 2.024846
Estimated effects may be unbalanced
鉴于警告，使用lm可能更安全:
Given the warning it might be safer to use lm:
> anova(lm(values ~ ind, mdat))
Analysis of Variance Table
Response: values
Df Sum Sq Mean Sq F value Pr(>F)
ind 3 18.2 6.0667 1.4797 0.2578
Residuals 16 65.6 4.1000
> summary(lm(values~ind, mdat))
Call:
lm(formula = values ~ ind, data = mdat)
Residuals:
Min 1Q Median 3Q Max
-3.40 -1.25 0.00 0.90 3.60
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.4000 0.9055 4.859 0.000174 ***
indb 0.8000 1.2806 0.625 0.540978
indc -1.2000 1.2806 -0.937 0.362666
indd -1.6000 1.2806 -1.249 0.229491
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2.025 on 16 degrees of freedom
Multiple R-squared: 0.2172, Adjusted R-squared: 0.07041
F-statistic: 1.48 on 3 and 16 DF, p-value: 0.2578
请不要问我为什么Excel会给出不同的答案.在统计方面，Excel通常被证明是高度不可靠的. Excel的责任是解释为什么它没有给出与R相当的答案.
And please don't ask me why Excel gives a different answer. Excel has generally been shown to be highly unreliable when it comes to statistics. The onus is on Excel to explain why it doesn't give answers comparable to R.
根据评论进行Excel Data Analysis Pack ANOVA过程创建一个输出，但是该过程不使用Excel函数，因此，当您更改派生数据的数据单元格中的数据，然后单击F9或等效的菜单重新计算命令，输出部分将保持不变. David Heiser在通过统计计算评估Excel问题的努力的各个页面中记录了用户和数字问题的各种来源: 2008年6月发行的计算统计与应用统计"中，还有一个特殊的6节.由BD McCullough编辑的数据分析" ，涵盖了Excel的各种统计问题.
Edit in response to comments: The Excel Data Analysis Pack ANOVA procedure creates an output but it does not use an Excel function for that process, so when you change the data in the data cells from which it was derived, and then hit F9, or the equivalent menu recalculation command, there will be no change in the output section. This and other sources of user and numerical problems are documented in various pages of David Heiser's efforts at assessing Excel's problems with statistical calculations: http://www.daheiser.info/excel/frontpage.html Heiser started out his efforts which are now at least a decade-long, with the expectation that Microsoft would take responsibility for these errors, but they have consistently ignored his and others' efforts at identifying errors and suggesting better procedures. There was also a 6 section Special Report in the June 2008 issue of "Computational Statistics & Data Analysis" edited by BD McCullough that cover various statistical concerns with Excel.
这篇关于如何使用按栏组织的样本在R中执行单因素ANOVA?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
