Displaying 13 results from an estimated 13 matches for "druga".
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2018 Mar 05
5
data analysis for partial two-by-two factorial design
David:
I believe your response on SO is incorrect. This is a standard OFAT (one
factor at a time) design, so that assuming additivity (no interactions),
the effects of drugA and drugB can be determined via the model you rejected:
For example, if baseline control (no drugs) has a response of 0, drugA has
an effect of 1, drugB has an effect of 2, and the effects are additive,
with no noise we would have:
> d <- data.frame(drugA = c("n","y",&qu...
2018 Mar 05
2
data analysis for partial two-by-two factorial design
...On Mar 5, 2018, at 2:27 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> >
> > David:
> >
> > I believe your response on SO is incorrect. This is a standard OFAT (one
> factor at a time) design, so that assuming additivity (no interactions),
> the effects of drugA and drugB can be determined via the model you rejected:
>
> >> three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug
> B, omitting the fourth group of no drugA/yes drugB.
>
> >
> > For example, if baseline control (no drugs) has a response of 0, drugA...
2018 Mar 05
0
data analysis for partial two-by-two factorial design
> On Mar 5, 2018, at 2:27 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
>
> David:
>
> I believe your response on SO is incorrect. This is a standard OFAT (one factor at a time) design, so that assuming additivity (no interactions), the effects of drugA and drugB can be determined via the model you rejected:
>> three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB.
>
> For example, if baseline control (no drugs) has a response of 0, drugA has an effect of 1, drugB...
2018 Mar 05
2
data analysis for partial two-by-two factorial design
...A + drug B). is it different from running three separate T tests?
Thank you so much!!
Ding
I need to analyze data generated from a partial two-by-two factorial design: two levels for drug A (yes, no), two levels for drug B (yes, no); however, data points are available only for three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB. I think we can not investigate interaction between drug A and drug B, can I still run model using R as usual: response variable = drug A + drug B? any suggestion is appreciated.
From: Bert Gun...
2018 Mar 05
0
data analysis for partial two-by-two factorial design
...> > On Mar 5, 2018, at 2:27 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> >
> > David:
> >
> > I believe your response on SO is incorrect. This is a standard OFAT (one factor at a time) design, so that assuming additivity (no interactions), the effects of drugA and drugB can be determined via the model you rejected:
>
> >> three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB.
>
> >
> > For example, if baseline control (no drugs) has a response of 0, drugA ha...
2018 Mar 05
0
data analysis for partial two-by-two factorial design
...es to add both A and B drugs. After drug treatments, they measure DNA methylation and genes or gene expression as outcome or response variables(two differnet types of response variables).
My boss might want to find out net effect of drug B, but I think we can not exclude the confounding effect of drugA. For example, it is possible that drug B has no effect, only has effect when drug A is present. I asked my collaborator whey she omitted the fourth combination drugA only treatment, she said it was expensive to measure methylation or gene expression, so they performed the experiments based on the...
2018 Mar 05
0
data analysis for partial two-by-two factorial design
...from running three separate T tests?
>
> Thank you so much!!
>
> Ding
>
> I need to analyze data generated from a partial two-by-two factorial design: two levels for drug A (yes, no), two levels for drug B (yes, no); however, data points are available only for three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB. I think we can not investigate interaction between drug A and drug B, can I still run model using R as usual: response variable = drug A + drug B? any suggestion is appreciated.
Replied on Cros...
2018 Mar 02
3
data analysis for partial two-by-two factorial design
Dear R users,
I need to analyze data generated from a partial two-by-two factorial design: two levels for drug A (yes, no), two levels for drug B (yes, no); however, data points are available only for three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB. I think we can not investigate interaction between drug A and drug B, can I still run model using R as usual: response variable = drug A + drug B? any suggestion is appreciated.
Thank you very...
2018 Mar 02
0
data analysis for partial two-by-two factorial design
...34 AM, Ding, Yuan Chun <ycding at coh.org> wrote:
> Dear R users,
>
> I need to analyze data generated from a partial two-by-two factorial
> design: two levels for drug A (yes, no), two levels for drug B (yes, no);
> however, data points are available only for three groups, no drugA/no
> drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group
> of no drugA/yes drugB. I think we can not investigate interaction between
> drug A and drug B, can I still run model using R as usual: response
> variable = drug A + drug B? any suggestion is appreciat...
2011 Oct 20
3
Survival analysis
Hello,
I need some results from the survival analysis of my data
that I do not know whether exist in Survival Package or how to obtain if
they do:
1. The Mean survival time
2. The standard error of the mean
3. Point and 95% Lower & Upper Confidence Intervals estimates
Any help will be greatly appreciated.
Cem
[[alternative HTML version
2009 Oct 27
0
syntax for estimable(gmodels package) and glht(multcomp package)
..., especially with models with 2nd order
terms.
A modestly complex model:
2-way anova with one continuous covariate, no random effects(and no
repeated measures) to keep it modestly complex:
Y = treatmentgroup + sex + treatmentgroup*sex + weight
treatment has 3 levels : "Placebo" , "DrugA" , "DrugB"
sex has 2 levels
I want to do pairwise comparison(s) for one of the main effects, say
"DrugB" - "Placebo"
And a pairwise comparison at the cell-wise level, for example:
"Female:DrugA" - "Female:Placebo" or
"Female:DrugA"...
2011 Oct 17
3
Extracting results from a function output
...rom a function. "fit" is a survival
function that produces some results, such as "median", "confidence
intervals" etc. But str() function does not list these values. How can I
extract these to be able use them? For example, I need "median" value for
the group DrugA which is 48. "Print" function does not reveal them either.
Thank you.
> fit
Call: survfit(formula = Surv(tT, dT) ~ gT, conf.type = "log-log")
records n.max n.start events median 0.95LCL 0.95UCL
gT=DrugA 9 9 9 6 48 32 NA
gT=DrugB 9 9 9 3 NA 42 NA
gT=DrugC 9 9 9 4 NA 42 NA
g...
2013 Oct 16
3
How to disable Internal call ?
Dear All,
I want to disable internal call facility.Means agent(4002) does not make
call to agent(4003) or other extensions.
Regards
Akhilesh
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