That said,
> wilcox_test(x ~ factor(y), distribution = "exact")
or the same with oneway_test, i.e would be ok?
2013/1/27 Achim Zeileis
> On Sun, 27 Jan 2013, Kay Cichini wrote:
>
> Thanks for the reply!
>>
>> Still, aren't there issues with 2-sample test vs y and excess zeroes
>> (->many ties), like for Mann-Whitney-U tests?
>>
>
> If you use the (approximate) exact distribution, that is no problem.
>
> The problem with the Wilcoxon/Mann-Whitney test and ties is only that the
> simple recursion formula for computing the exact distribution only works
> without ties. Thus, it's not the exact distribution that is wrong but only
> the standard algorithm for evaluating it.
>
> Best,
> Z
>
> Kind regards,
>> Kay
>>
>>
>> 2013/1/26 Achim Zeileis
>>
>> On Fri, 25 Jan 2013, Kay Cichini wrote:
>>>
>>> Hello,
>>>
>>>>
>>>> I'm searching for a test that applies to a dataset (N=36) with a
>>>> continuous zero-inflated dependent variable
>>>>
>>>>
>>> In a regression setup, one can use a regression model with a response
>>> censored at zero. survreg() in survival fits such models, tobit() in AER
>>> is
>>> a convenience interface for this special case.
>>>
>>> If the effects of a regressor can be different for the probability of a
>>> zero and the mean of the non-zero observations, then a two-part model can
>>> be used. E.g. a probit fit (via glm) plus a truncated regression (via
>>> truncreg in the package of the same name).
>>>
>>> However:
>>>
>>>
>>> and only one nominal grouping variable with 2 levels (balanced).
>>>
>>>>
>>>>
>>> In that case I would probably use no regression model but two-sample
>>> permutation tests, e.g. via the "coin" package.
>>>
>>>
>>> In fact there are 4 response variables of this kind which I plan to test
>>>
>>>> seperately - the amount of zeroes ranges from 75 to 97%..
>>>>
>>>>
>>> That means you have between one (!) and nine non-zero observations. In
>>> the
>>> former case, it will be hard to model anything. And even in the latter
>>> case
>>> it will be hard to investigate the probability of zero and the mean of
>>> the
>>> non-zero observations separately.
>>>
>>> I would start out with a simple two-way table of (y > 0) vs group and
>>> conduct Fisher's exact test.
>>>
>>> And then you might try also your favorite two sample test of y vs group,
>>> preferably using the approximate exact distribution.
>>>
>>> Hope that helps,
>>> Z
>>>
>>> I searched the web and found several modelling approaches but have the
>>>
>>>> feeling that they are overly complex for my very simple dataset.
>>>>
>>>> Thanks in advance for any help!
>>>> Kay
>>>>
>>>> --
>>>>
>>>> Kay Cichini, MSc Biol
>>>>
>>>> Grubenweg 22, 6071 Aldrans
>>>>
>>>> Tel.: 0650 9359101
>>>>
>>>> E-Mail: kay.cichini@gmail.com
>>>>
>>>> Web: www.theBioBucket.blogspot.co.****at>>> blogspot.co.at >
>>>> <
>>>> http://www.**thebiobucket.blogspot.co.at/
>>>> >
>>>>
>>>>>
>>>>>
>>>>> >
>>>>>
>>>>> --
>>>>
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>>>>
>>>> ______________________________****________________
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>>>>
>>>> >
>>>> PLEASE do read the posting guide http://www.R-project.org/**
>>>> posting-guide.html
>>>> >
>>>>
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>>
>>>>
>>
>> --
>>
>> Kay Cichini, MSc Biol
>>
>> Grubenweg 22, 6071 Aldrans
>>
>> Tel.: 0650 9359101
>>
>> E-Mail: kay.cichini@gmail.com
>>
>> Web: www.theBioBucket.blogspot.co.**at
>>
>> >
>> >
>> --
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________**________________
>> R-help@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.
>>
>>
--
Kay Cichini, MSc Biol
Grubenweg 22, 6071 Aldrans
Tel.: 0650 9359101
E-Mail: kay.cichini@gmail.com
Web: www.theBioBucket.blogspot.co.at
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