Results 231 to 240 of about 1,303,019 (294)

Discrimination between alternative binary response models

Biometrika, 1967
SUMMARY The logistic and integrated normal binary response curves are known to agree closely except in the tails. For experiments based on three dose levels the power of a significance test is found for the null hypothesis that the response curve is logistic against the alternative that it is normal, and vice versa.
E A, Chambers, D R, Cox
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COVARIATE-ADJUSTED RESPONSE-ADAPTIVE DESIGNS FOR BINARY RESPONSE

Journal of Biopharmaceutical Statistics, 2001
An adaptive allocation design for phase III clinical trials that incorporates covariates is described. The allocation scheme maps the covariate-adjusted odds ratio from a logistic regression model onto [0, 1]. Simulations assume that both staggered entry and time to response are random and follow a known probability distribution that can depend on the ...
W F, Rosenberger, A N, Vidyashankar, D K, Agarwal   +2 more
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Binary response data

2009
Abstract Much social science data consist of categorical variables. Familiar examples are religion, nationality, residence (urban/rural), type of dwelling, level of education and social class. The categories may be unordered (religion, nationality) or ordered (degree of disablement, attitude to a social question).
Murray Aitkin, Brian Francis, John Hinde, Ross Darnell   +3 more
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Network and covariate adjusted response‐adaptive design for binary response

Statistics in Medicine, 2023
Randomization is a distinguishing feature of clinical trials for unbiased assessment of treatment efficacy. With a growing demand for more flexible and efficient randomization schemes and motivated by the idea of adaptive design, in this article we propose the network and covariate adjusted response‐adaptive (NCARA) design that can concurrently manage ...
Hao Mei, Jiaxin Xie, Yichen Qin, Yang Li
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Binary response data

2005
Abstract Much social science data consist of categoricalvariables. Familiar examples are religion, nationality, residence (urban/rural), type of dwelling, level of education and social class. The categories may be unordered (religion, nationality) or ordered (degree of disablement, attitude to a social question).
Murray Aitkin, Brain Francis, John Hinde
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Optimal Adaptive Designs for Binary Response Trials

Biometrics, 2001
We derive the optimal allocation between two treatments in a clinical trial based on the following optimality criterion: for fixed variance of the test statistic, what allocation minimizes the expected number of treatment failures? A sequential design is described that leads asymptotically to the optimal allocation and is compared with the randomized ...
Rosenberger, William F., Stallard, Nigel, Ivanova, Anastasia, Harper, Cherice N., Ricks, Michelle L.   +4 more
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Testing for Independence of Binary Responses

Biometrical Journal, 1986
AbstractIn the context of experiments involving visual inspection of random dot patterns the problem of testing the null hypothesis of independence of binary responses is considered. A flexible model for dependence between binary responses is proposed. Two tests, optimal under different versions of the model, are derived.
FIDLER, [No Value], DEJONGE, AB
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Association Models for a Multivariate Binary Response

Biometrics, 2000
Summary.Models for a multivariate binary response are parameterized by univariate marginal proba‐bilities and dependence ratios of all orders. Thew‐order dependence ratio is the joint success probability ofwbinary responses divided by the joint success probability assuming independence. This parameterization supports likelihood‐based inference for both
Ekholm, Anders, McDonald, John W., Smith, Peter W.F.   +2 more
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