[R] output from multcomp and lm
Hiroto Miyoshi
h_m_ at po.harenet.ne.jp
Tue Feb 3 02:46:41 CET 2004
Dear R-users
I analysed the same data set by two different ways;
analysis of covariance by using lm and anova functions
and multiple comparison by using simtest function in
the multcomp library.
The output from the analysis of covariance is;
> y<-lm(D~Cond+Q1,data=x)
> anova(y)
Analysis of Variance Table
Response: D
Df Sum Sq Mean Sq F value Pr(>F)
Cond 2 1017.8 508.9 4.7548 0.0135041 *
Q1 1 1652.7 1652.7 15.4417 0.0002969 ***
Residuals 44 4709.2 107.0
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
where Cond is a factor with three levels (A,B,C)
and Q1 is a covariate.
Now, simtest showed the following output
> o5<-summary(simtest(D~Cond+Q1,conf.level=0.95,data=x,type="Tukey"))
> o5
Simultaneous tests: Tukey contrasts
Call:
simtest.formula(formula = D ~ Cond + Q1, data = x, conf.level = 0.95,
type = "Tukey")
Tukey contrasts for factor Cond, covariable: Q1
Contrast matrix:
CondA CondB CondC
CondB-CondA 0 -1 1 0 0
CondC-CondA 0 -1 0 1 0
CondC-CondB 0 0 -1 1 0
Absolute Error Tolerance: 0.001
Coefficients:
Estimate t value Std.Err. p raw p Bonf p adj
CondB-CondA 5.555 -1.461 3.802 0.151 0.453 0.319
CondC-CondB -5.248 -1.365 3.661 0.179 0.453 0.319
CondC-CondA 0.306 -0.084 3.844 0.934 0.934 0.934
The results from two analyses seem so different that I am
wondering why. I do understand that multiple comparison may
not show any significant difference even when the overall analysis
of (co)variance shows the statistical significance of a factor.
However, in my analysis, overall analysis showed statistical significance of
1.4% level and mutiple comparison showed significance of 32% level
Could this happen? and why? Please enlighten me.
Sincerely
------------------------
Hiroto Miyoshi
三好弘人
h_m_ at po.harenet.ne.jp
More information about the R-help
mailing list