2013-02-28 99 views
2

是否有简单的方法来对汇总元素进行后续数学计算?我有通过anova分析运行的日志转换数据。我想计算汇总输出的反对数。对汇总元素进行计算

我有以下代码:

require(multcomp) 
inc <- log(Inc) 
myanova <- aov(inc ~ educ)  
tukey <- glht(myanova, linfct = mcp(educ = "Tukey")) 
summary(tukey) 

如下产生一个输出:

     Estimate Std. Error t value Pr(>|t|)  
12 - under12 == 0  0.32787 0.08493 3.861 0.00104 ** 
13to15 - under12 == 0 0.49187 0.08775 5.606 < 0.001 *** 
16 - under12 == 0  0.89775 0.09217 9.740 < 0.001 *** 
over16 - under12 == 0 0.99856 0.09316 10.719 < 0.001 *** 
13to15 - 12 == 0  0.16400 0.04674 3.509 0.00394 ** 
etc. 

如何可以容易地在估计值来执行反对数计算?

+0

看看'属性(tukey)'' – 2013-02-28 04:57:05

回答

1

这是一个小问题,所以我建议进一步检查,但如果你想要看到指数估计和标准错误,我认为类似于下面的东西将工作(我使用不同的数据)。

> amod <- aov(breaks ~ tension, data = warpbreaks) 
> tukey = glht(amod, linfct = mcp(tension = "Tukey")) 

> tsum = summary(tukey) 
> tsum[[10]]$coefficients = exp(tsum[[10]]$coefficients) 
> tsum[[10]]$sigma = exp(tsum[[10]]$sigma) 
> tsum 

如果你想使用COEF(杜克),给你估计,你会扭转变换搭配:

exp(coef(tukey)) 
0

我认为这应该工作:

 coef(tukey) 

得到估计值。这里一个例子:

amod <- aov(breaks ~ tension, data = warpbreaks) 
    tukey <- glht(amod, linfct = mcp(tension = "Tukey")) 

现在,如果想让你输入你申请headtail获得与摘要元素命名列表中的所有杜克摘要元素。

head(summary(tukey)) 
$model 
Call: 
    aov(formula = breaks ~ tension, data = warpbreaks) 

Terms: 
       tension Residuals 
Sum of Squares 2034.259 7198.556 
Deg. of Freedom  2  51 

Residual standard error: 11.88058 
Estimated effects may be unbalanced 

$linfct 
     (Intercept) tensionM tensionH 
M - L   0  1  0 
H - L   0  0  1 
H - M   0  -1  1 
attr(,"type") 
[1] "Tukey" 

$rhs 
[1] 0 0 0 

$coef 
(Intercept) tensionM tensionH 
    36.38889 -10.00000 -14.72222 

$vcov 
      (Intercept) tensionM tensionH 
(Intercept) 7.841564 -7.841564 -7.841564 
tensionM  -7.841564 15.683128 7.841564 
tensionH  -7.841564 7.841564 15.683128 

$df 
[1] 51