Displaying 5 results from an estimated 5 matches for "trtc".
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rtc
2013 Jan 27
1
decimal places in R2HTML
Dear R People:
I have an AOV model that I get confidence intervals from via
> confint(chick1.aov1)
2.5 % 97.5 %
trtA 1.472085 1.607915
trtB 1.512085 1.647915
trtC 1.328751 1.464582
>
I am using R2HTML to produce HTML output. However, the HTML code
itself just has rounded values, i.e., 1.5 and 1.6.
Has anyone run across this, please?
Any suggestions would be much appreciated.
Sincerely,
Erin
--
Erin Hodgess
Associate Professor
Department of Computer...
2007 Oct 22
2
Repeated Measures/Linear Mixed Effects function
...this. I
have searched in vain and cannot find the answer. Any help or links to
examples would be appreciated greatly.
Fixed effects: Xc ~ trt
Value Std.Error DF t-value p-value
(Intercept) 103.62 2.619657 20 39.55480 0
trtB -33.28 1.991197 20 -16.71356 0
trtC -39.38 1.991197 20 -19.77705 0
trtD -32.60 1.991197 20 -16.37206 0
trtE -47.32 1.991197 20 -23.76460 0
trtF -39.58 1.991197 20 -19.87749 0
Xc
Trt
fish
109.1
a
1
73
b
1
68.4
c
1
74.8
d
1
60.3
e
1
57
f
1
106...
2008 Apr 15
2
glht with a glm using a Gamma distribution
Quick question about the usage of glht. I'm working with a data set
from an experiment where the response is bounded at 0 whose variance
increases with the mean, and is continuous. A Gamma error
distribution with a log link seemed like the logical choice, and so
I've modeled it as such.
However, when I use glht to look for differences between groups, I get
significant
1999 Nov 30
3
model.tables
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2011 Apr 21
1
Accounting for overdispersion in a mixed-effect model with a proportion response variable and categorical explanatory variables.
...6 ***
treatmentB 0.16590 0.06356 2.610 0.00904 **
treatmentC 0.01642 0.06784 0.242 0.80878
treatmentD 0.26677 0.06710 3.976 7.01e-05 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Correlation of Fixed Effects:
(Intr) tBPBS_ tCPBS_
trtB -0.711
trtC -0.666 0.474
trtD -0.674 0.479 0.449
>
I then compared the 2 models.
> anova(model,model2,test="F")
Data:
Models:
model: y ~ treatment + (1 | treatment/mouse)
model2: y ~ treatment + (1 | treatment/mouse) + (1 | obs)
Df AIC BIC logLik Chisq Chi Df Pr(>Chisq)...