Displaying 6 results from an estimated 6 matches for "treatmentc".
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2009 Oct 26
1
explalinig the output of my linear model analysis
...Max
-58.905 -19.958 -5.774 16.693 88.890
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 55.4664 2.0332 27.281 < 2e-16 ***
a$habitats -11.9615 2.8753 -4.160 3.26e-05 ***
a$habitate:a$treatmentc 7.3581 2.8753 2.559 0.01054 *
a$habitats:a$treatmentc -4.9803 2.8753 -1.732 0.08335 .
a$habitate:a$treatmentp -13.9906 2.8753 -4.866 1.19e-06 ***
a$habitats:a$treatmentp -16.1311 2.8753 -5.610 2.17e-08 ***
a$habitate:a$treatmenta:a$trial...
2011 Sep 13
1
stupid lm() question
I feel bad even asking, but:
Rgames> data(OrchardSprays)
Rgames> model<-lm(decrease~.,data=OrchardSprays)
Rgames> model
Call:
lm(formula = decrease ~ ., data = OrchardSprays)
Coefficients:
(Intercept) rowpos colpos treatmentB treatmentC
22.705 -2.784 -1.234 3.000 20.625
treatmentD treatmentE treatmentF treatmentG treatmentH
30.375 58.500 64.375 63.875 85.625
Rgames> levels(OrchardSprays$treatment) #just double-checking...
[1] "A" "B" &...
2008 Jul 30
1
Mixed effects model where nested factor is not the repeated across treatments lme???
...ects:
Formula: ~1 | block
(Intercept) Residual
StdDev: 0.4306096 0.9450976
Fixed effects: Cu ~ Treatment
Value Std.Error DF t-value p-value
(Intercept) 5.587839 0.2632831 104 21.223688 0.0000 ***
TreatmentB -0.970384 0.3729675 16 -2.601792 0.0193 ***
TreatmentC -1.449250 0.3656351 16 -3.963651 0.0011 ***
TreatmentD -1.319564 0.3633837 16 -3.631323 0.0022 ***
Correlation:
(Intr) TrtmAN TrtmCH
TreatmentB -0.706
TreatmentC -0.720 0.508
TreatmentD -0.725 0.511 0.522
Standardized Within-Group Residuals:...
2011 Apr 21
1
Accounting for overdispersion in a mixed-effect model with a proportion response variable and categorical explanatory variables.
...eviance Residuals:
Min 1Q Median 3Q Max
-2.3134 -0.5712 -0.3288 0.8616 2.4352
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.574195 0.036443 -15.756 < 2e-16 ***
treatmentB 0.164364 0.051116 3.216 0.00130 **
treatmentC 0.007025 0.054696 0.128 0.89780
treatmentD 0.258135 0.053811 4.797 1.61e-06 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 60.467 on 17 degrees of freedom
Residual deviance: 28.711 on...
2006 Jun 09
0
interaction terms in regression analysis
...re stored as follows:
expt treatA treatB dose force
I use a groupedData object mydata=groupedData(force ~ dose | expt)
I used an nlme obect to model the data as follows (pseudocode):
myfit <- nlme(force ~ ssThreeParLogistic(dose, upper, ed50,slope),
fixed=list(ed50~factor(treatmentA)*factor(treatmentC)))
The ThreeParLogistic is a properly debugged and fully functional
selfstarting object that I wrote- no problem here. I also included
terms for the other terms; upper and slope, but my main focus is on the
ed50 so that's all I've included here
Running an anova on the resulting object...
2008 Jan 24
2
testing coeficients of glm
Dear list,
i'm trying to test if a linear combination of coefficients of glm is equal
to 0. For example :
class 'cl' has 3 levels (1,2,3) and 'y' is a response variable. We want to
test H0: mu1 + mu2 - mu3 =0 where mu1,mu2, and mu3 are the means for each
level.
for me, the question is how to get the covariance matrix of the estimated
parameters from glm. but perhaps there