Thanks for the reply Peter,
> I did just see that i had put the first error message,(agreed rather an
> obvious error) in and not the second i received
>
> Warning message:
> In asin(sqrt(yF[i])) : NaNs produced
>
> The reason i'm looking at this is advert exposure True and False.
>
> I'm inspecting age to asses weather or not to weight data in order to
> normalise groups for later questions,
> The questions that i am looking at later on are not scale based questions
> so i cannot perform t-tests on these, so i thought the only viable way was
> to look at z-tests for proportions to check for post-hoc differences
>
> Any advise on other methods would be gratefully taken
>
>
>
> On Fri, Jun 20, 2008 at 11:14 AM, Peter Dalgaard
<P.Dalgaard@biostat.ku.dk>
> wrote:
>
>> Michael Pearmain wrote:
>> > I'm having trouble creating a looping variable and i can't
see wher ethe
>> > problem arises from any hep gratfully appreciated
>> >
>> > First create a table
>> >
>> > x<-table(SURVEY$n_0,exposed)
>> >
>> >> x
>> >>
>> > exposed
>> > False True
>> > Under 16 24 1
>> > 16-19 68 9
>> > 20-24 190 37
>> > 25-34 555 204
>> > 35-44 330 87
>> > 45-54 198 65
>> > 55-64 67 35
>> > 65+ 10 8
>> >
>> > Now ectors to store counts and column proportions
>> >
>> >
>> >> xT<-x[,"True"]
>> >> xF<-x[,"False"]
>> >> yT<-x[,"True"]/colSums(x)
>> >> yF<-x[,"False"]/colSums(x)
>> >>
>> >
>> > check length for dynamic looping
>> >
>> >> length(yT)
>> >>
>> > [1] 8
>> >
>> > now create loop
>> >
>> >> for(i in 1:length(yT)){
>> >>
>> > +
>>
pwr.2p2n.test(2*(asin(sqrt(yT[i]))-asin(sqrt(yF[i]))),n1=xT[i],n2=xF[i])
>> > + }
>> > Error in pwr.2p2n.test(2 * (asin(sqrt(yT[i])) -
asin(sqrt(yF[i]))), n1 >> > xT[i], :
>> > number of observations in the first group must be at least 2
>> >
>> > this confuses me as if i enter the data as values the procedure
works?
>> >
>> > Thanks in advance
>> >
>> Er, the first row "under 16" has a count of 1 in the
"True" column and
>> it confuses you that you get an error saying that you need at least 2??
>>
>> But what looks _really_ confused is what you are trying to do in the
>> first place: The p's you are passing to pwr.2p2n are the empirical
>> relative frequencies of the individual age groups. This sort of
reverses
>> cause and effect (presumably the exposure does not cause middle age)
and
>> it is pretty odd to compare a particular row in a table with
everything
>> else jumbled together but worse, it is post-hoc power calculation,
which
>> is just a plain Bad Idea (as several people have pointed out before).
>>
>> --
>> O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
>> c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
>> (*) \(*) -- University of Copenhagen Denmark Ph: (+45)
35327918
>> ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk) FAX: (+45)
35327907
>>
>>
>>
>
>
> --
> Michael Pearmain
> Senior Statistical Analyst
>
>
> 1st Floor, 180 Great Portland St. London W1W 5QZ
> t +44 (0) 2032191684
> mpearmain@google.com
> mpearmain@doubleclick.com
>
>
> Doubleclick is a part of the Google group of companies
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