Experimental design for binary data

K. M. Abdelbasit, R. L. Plackett

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

158 اقتباسات (Scopus)


Models for binary data are usually such that the information matrix depends on the unknown parameters. Thus the standard criteria for optimality in regression experiments cannot be applied without modification. Methods of going around this difficulty include the use of initial point estimates, sequential methods, and Bayesian analysis. This article is mainly concerned with the robustness and the number of design points for methods involving initial estimates, and for sequential methods in a small number of stages. A final section discusses the criterion of constant information for models involving one or two parameters, and summarizes recent results in this field.

اللغة الأصليةEnglish
الصفحات (من إلى)90-98
عدد الصفحات9
دوريةJournal of the American Statistical Association
مستوى الصوت78
رقم الإصدار381
المعرِّفات الرقمية للأشياء
حالة النشرPublished - مارس 1983
منشور خارجيًانعم

ASJC Scopus subject areas

  • ???subjectarea.asjc.2600.2613???
  • ???subjectarea.asjc.1800.1804???


أدرس بدقة موضوعات البحث “Experimental design for binary data'. فهما يشكلان معًا بصمة فريدة.

قم بذكر هذا