[R list package] p value in test for design effects

[Kosuke Imai]

Sorry. I meant to say "min" rather than "max"!

Kosuke Imai
Department of Politics
Princeton University
http://imai.princeton.edu

On Mon, Jul 27, 2015 at 7:58 AM, Kosuke Imai <kimai at princeton.edu> wrote:

> Hi Felix,
>
>   It's a typo in the output: the pvalue should be max(bonferroni.p-value,
> 1).  So, your p-value is 1.  This can be seen from the fact that your
> estimate is never negative.  The test based on design effects flags when
> these estimates of proportions become negative (proportions should always
> be non-negative).  The question is when that occurs whether or not a
> negative value is within sampling error.  Hope this makes sense.  We will
> fix the package soon.
>
> Best,
> Kosuke
>
> ---------------------------------------------------------
> Kosuke Imai               Office: Corwin Hall 036
> Professor                 Phone: 609-258-6601
> Department of Politics    Fax: 609-258-1110
> Princeton University      Email: kimai at Princeton.Edu
> Princeton, NJ 08544-1012  http://imai.princeton.edu
> ---------------------------------------------------------
>
> On Mon, Jul 27, 2015 at 7:48 AM, Felix Wolter <felix.wolter at uni-mainz.de>
> wrote:
>
>> Hello everybody,
>>
>> we have encountered some problems using the test for design effects in
>> the list package. The outcome is pasted below. We would be very happy if
>> someone could help us with the interpretation of the p-value of 1.227,
>> which is greater than 1. Does this make sense? Or is the data unsuited for
>> this test - as you can see, the distribution is heavily skewed with many
>> respondents answering "0" (this is due to a special design of our ICT
>> procedure).
>>
>> Thank you very much in advance!
>> And kind greetings
>>
>> Felix
>>
>>
>> > test.value.aushei <- ict.test(aushei$y, aushei$pct, J = 3, alpha=0.05,
>> gms = TRUE, pi.table = TRUE)
>> > print(test.value.aushei)
>>
>> Test for List Experiment Design Effects
>>
>> Estimated population proportions
>>                    est.   s.e.
>> pi(y = 0, t = 1) 0.1178 0.0418
>> pi(y = 1, t = 1) 0.0356 0.0245
>> pi(y = 2, t = 1) 0.0067 0.0104
>> pi(y = 3, t = 1) 0.0045 0.0045
>> pi(y = 0, t = 0) 0.7364 0.0297
>> pi(y = 1, t = 0) 0.0686 0.0345
>> pi(y = 2, t = 0) 0.0280 0.0184
>> pi(y = 3, t = 0) 0.0024 0.0083
>>
>> Bonferroni-corrected p-value
>> If this value is below alpha, you reject the null hypothesis of no design
>> effect. If it is above alpha, you fail to reject the null.
>>
>> Sensitive Item 1
>>         1.227221
>>
>>
>>
>> --
>> Dr. Felix Wolter
>> Institut für Soziologie
>> Johannes Gutenberg-Universität Mainz
>> Georg-Forster-Gebäude, Raum 03-446
>> Jakob-Welder-Weg 12
>> D-55128 Mainz
>>
>> Tel: 06131 - 39 20831
>> Fax: 06131 - 39 26157
>> Mail: felix.wolter at uni-mainz.de
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>>
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>>
>
>
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