{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T09:25:01Z","timestamp":1751534701118,"version":"3.41.0"},"reference-count":19,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2014,5,2]],"date-time":"2014-05-02T00:00:00Z","timestamp":1398988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Model. Comput. Simul."],"published-print":{"date-parts":[[2014,5,2]]},"abstract":"<jats:p>The sample size decision is crucial to the success of any sampling experiment. More samples imply better confidence and precision in the results, but require higher costs in terms of time, computing power, and money. Analysts often choose sequential stopping rules on an ad hoc basis to obtain confidence intervals with desired properties without requiring large sample sizes. However, the choice of stopping rule can affect the quality of the interval produced in terms of the coverage, precision, and replication cost. This article introduces methods for choosing and evaluating stopping rules for confidence interval procedures. We develop a general framework for assessing the quality of a broad class of stopping rules applied to independent and identically distributed data. We introduce coverage profiles that plot the coverage according to the stopping time and reveal situations when the coverage could be unexpectedly low. Finally, we recommend simple techniques for obtaining acceptable or optimal rules.<\/jats:p>","DOI":"10.1145\/2627734","type":"journal-article","created":{"date-parts":[[2014,7,28]],"date-time":"2014-07-28T13:21:33Z","timestamp":1406553693000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Selecting Stopping Rules for Confidence Interval Procedures"],"prefix":"10.1145","volume":"24","author":[{"given":"Dashi I.","family":"Singham","sequence":"first","affiliation":[{"name":"Naval Postgraduate School, Monterey CA"}]}],"member":"320","published-online":{"date-parts":[[2014,7,25]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1057\/jos.2011.23"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177700156"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoap\/1177005777"},{"key":"e_1_2_1_4_1","article-title":"Modified t tests and confidence intervals for asymmetrical populations","volume":"73","author":"Johnson N. J.","year":"1978","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.38.3.546"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/502109.502111"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.27.5.1011"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.28.5.550"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177697737"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1957.tb00248.x"},{"key":"e_1_2_1_11_1","unstructured":"H. Robbins. 1959. Sequential estimation of the mean of a normal population. In U. Grenander (ed.) Probability and Statistics; The Harald Cram\u00e9r Volume. Almquist & Wiksell and John Wiley and Sons New York 235--245.  H. Robbins. 1959. Sequential estimation of the mean of a normal population. In U. Grenander (ed.) Probability and Statistics; The Harald Cram\u00e9r Volume. Almquist & Wiksell and John Wiley and Sons New York 235--245."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.40.5.898"},{"volume-title":"Proceedings of the 2002 Winter Simulation Conference. IEEE, 345--352","author":"Schmeiser B.","key":"e_1_2_1_13_1"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.26.1.18"},{"volume-title":"Proceedings of the 2009 Winter Simulation Conference. IEEE, 724--730","author":"Singham D. 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