Re: [R] Testing continuous zero-inflated response

2013-01-28 Thread Kay Cichini
Many thanks - this was very helpful! Regards, Kay Am 28.01.2013 13:19 schrieb "Achim Zeileis" : > On Sun, 27 Jan 2013, Kay Cichini wrote: > > That said, >> >> wilcox_test(x ~ factor(y), distribution = "exact") >>> >> >> or the same with oneway_test, i.e would be ok? >> > > Yep, exactly. > > And

Re: [R] Testing continuous zero-inflated response

2013-01-28 Thread Achim Zeileis
On Sun, 27 Jan 2013, Kay Cichini wrote: That said, wilcox_test(x ~ factor(y), distribution = "exact") or the same with oneway_test, i.e would be ok? Yep, exactly. And you could also look at chisq_test(factor(x > 0) ~ factor(y), distribtuion = approximate()) or something like that. Or

Re: [R] Testing continuous zero-inflated response

2013-01-27 Thread Kay Cichini
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 tie

Re: [R] Testing continuous zero-inflated response

2013-01-27 Thread 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 tes

Re: [R] Testing continuous zero-inflated response

2013-01-27 Thread Kay Cichini
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? 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=

Re: [R] Testing continuous zero-inflated response

2013-01-25 Thread 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()