<div dir="ltr">Hi Felix,<div><br></div><div> 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.</div><div><br></div><div>Best,</div><div>Kosuke</div><div><br></div><div>---------------------------------------------------------<br>Kosuke Imai Office: Corwin Hall 036<br>Professor Phone: 609-258-6601<br>Department of Politics Fax: 609-258-1110<br>Princeton University Email: kimai@Princeton.Edu<br>Princeton, NJ 08544-1012 <a href="http://imai.princeton.edu">http://imai.princeton.edu</a><br>---------------------------------------------------------<br><br></div><div class="gmail_extra"><div class="gmail_quote">On Mon, Jul 27, 2015 at 7:48 AM, Felix Wolter <span dir="ltr"><<a href="mailto:felix.wolter@uni-mainz.de" target="_blank">felix.wolter@uni-mainz.de</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hello everybody,<br>
<br>
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).<br>
<br>
Thank you very much in advance!<br>
And kind greetings<br>
<br>
Felix<br>
<br>
<br>
> test.value.aushei <- ict.test(aushei$y, aushei$pct, J = 3, alpha=0.05, gms = TRUE, pi.table = TRUE)<br>
> print(test.value.aushei)<br>
<br>
Test for List Experiment Design Effects<br>
<br>
Estimated population proportions<br>
est. s.e.<br>
pi(y = 0, t = 1) 0.1178 0.0418<br>
pi(y = 1, t = 1) 0.0356 0.0245<br>
pi(y = 2, t = 1) 0.0067 0.0104<br>
pi(y = 3, t = 1) 0.0045 0.0045<br>
pi(y = 0, t = 0) 0.7364 0.0297<br>
pi(y = 1, t = 0) 0.0686 0.0345<br>
pi(y = 2, t = 0) 0.0280 0.0184<br>
pi(y = 3, t = 0) 0.0024 0.0083<br>
<br>
Bonferroni-corrected p-value<br>
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.<br>
<br>
Sensitive Item 1<br>
1.227221<br>
<br>
<br>
<br>
-- <br>
Dr. Felix Wolter<br>
Institut für Soziologie<br>
Johannes Gutenberg-Universität Mainz<br>
Georg-Forster-Gebäude, Raum 03-446<br>
Jakob-Welder-Weg 12<br>
D-55128 Mainz<br>
<br>
Tel: 06131 - 39 20831<br>
Fax: 06131 - 39 26157<br>
Mail: <a href="mailto:felix.wolter@uni-mainz.de" target="_blank">felix.wolter@uni-mainz.de</a><br>
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</blockquote></div><br></div></div>