[R] Random assignment

[Michael Bedward]

Hi John,

The word "species" attracted my attention :)

Like Dennis, I'm not sure I understand your idea properly. In
particular, I don't see what you need the simulation for.

If family F has Fn species, your random expectation is that p * Fn of
them will be at risk (p = 0.0748). The variance on that expectation
will be p * (1-p) * Fn.

If you do your simulation that's the result you'll get.  Perhaps to
initial identify families with disproportionate observed extinction
rates all you need is the dbinom function ?

Michael


On 15 October 2010 22:29, John Haart <another83 at me.com> wrote:
> Hi Denis and list
>
> Thanks for this , and sorry for not providing enough information
>
> First let me put the study into a bit more context : -
>
> I know the number of species at risk in each family, what i am asking  is "Is risk random according to family or do certain families have a disproportionate number of at risk species?"
>
> My idea was to randomly allocate risk to the families based on the criteria below (binomial(nspecies, 0.0748)) and then compare this to the "true data" and see if there was a significant difference.
>
> So in answer to your questions, (assuming my method is correct !)
>
>> Is this over all families, or within a particular family? If the former, why
>> does a distinction of family matter?
>
> Within a particular family  - this is because i am looking to see if risk in the "observed" data set is random in respect to family so this will provide the baseline to compare against.
>
>> I guess you've stated the p, but what's the n? The number of species in each
>> family?
>
> This varies largely, for instance i have some families that are monotypic  (with 1 species) and then i have other families with 100+ species
>
>
>> Assuming you have multiple families, do you want separate simulations per
>> family, or do you want to do some sort of weighting (perhaps proportional to
>> size) over all families?
>
> I am assuming i want some sort of weighting. This is because i am wanting to calculate the number of species expected to be at risk in EACH family under the random binomial distribution ( assuming every species has a 7.48% chance of being at risk.
>
> Thanks
>
> John
>
>
>
>
> On 15 Oct 2010, at 11:19, Dennis Murphy wrote:
>
> Hi:
>
> I don't believe you've provided quite enough information just yet...
>
> On Fri, Oct 15, 2010 at 2:22 AM, John Haart <another83 at me.com> wrote:
>
>> Dear List,
>>
>> I am doing some simulation in R and need basic help!
>>
>> I have a list of animal families for which i know the number of species in
>> each family.
>>
>> I am working under the assumption that a species has a 7.48% chance of
>> being at risk.
>>
>
> Is this over all families, or within a particular family? If the former, why
> does a distinction of family matter?
>
>>
>> I want to simulate the number of species expected to be at risk under a
>> random binomial distribution with 10,000 randomizations.
>>
>
> I guess you've stated the p, but what's the n? The number of species in each
> family? If you're simulating on a family by family basis, then it would seem
> that a binomial(nspecies, 0.0748) distribution would be the reference.
> Assuming you have multiple families, do you want separate simulations per
> family, or do you want to do some sort of weighting (perhaps proportional to
> size) over all families? The latter is doable, but it would require a
> two-stage simulation: one to randomly select a family and then to randomly
> select a species.
>
> Dennis
>
>
>>
>> I am relatively knew to this field and would greatly appreciate a
>> "idiot-proof" response, I.e how should the data be entered into R? I was
>> thinking of using read.table, header = T, where the table has F = Family
>> Name, and SP = Number of species in that family?
>>
>> John
>>
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>>
>
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>
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> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>