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Results: 1-25 |
Results: 25
A correlated probit model for joint modeling of clustered binary and continuous responses
Authors: Gueorguieva, RV Agresti, A
Citation: Rv. Gueorguieva et A. Agresti, A correlated probit model for joint modeling of clustered binary and continuous responses, J AM STAT A, 96(455), 2001, pp. 1102-1112
Experimental evidence of tunneling as a stochastic process - art. no. 025102
Authors: Ranfagni, A Ruggeri, R Susini, C Agresti, A Sandri, P
Citation: A. Ranfagni et al., Experimental evidence of tunneling as a stochastic process - art. no. 025102, PHYS REV E, 6302(2), 2001, pp. 5102
Interval estimation for a binomial proportion - Comment - Rejoinder
Authors: Brown, LD Cai, TT DasGupta, A Agresti, A Coull, BA Casella, G Corcoran, C Mehta, C Ghosh, M Santner, TJ Brown, LD Cai, TT DasGupta, A
Citation: Ld. Brown et al., Interval estimation for a binomial proportion - Comment - Rejoinder, STAT SCI, 16(2), 2001, pp. 101-133
Exact inference for categorical data: recent advances and continuing controversies
Authors: Agresti, A
Citation: A. Agresti, Exact inference for categorical data: recent advances and continuing controversies, STAT MED, 20(17-18), 2001, pp. 2709-2722
The double life of HMGB1 chromatin protein: architectural factor and extracellular signal
Authors: Muller, S Scaffidi, P Degryse, B Bonaldi, T Ronfani, L Agresti, A Beltrame, M Bianchi, ME
Citation: S. Muller et al., The double life of HMGB1 chromatin protein: architectural factor and extracellular signal, EMBO J, 20(16), 2001, pp. 4337-4340
Strategies for modeling a categorical variable allowing multiple category choices
Authors: Agresti, A Liu, I
Citation: A. Agresti et I. Liu, Strategies for modeling a categorical variable allowing multiple category choices, SOCIOL METH, 29(4), 2001, pp. 403-434
On small-sample confidence intervals for parameters in discrete distributions
Authors: Agresti, A Min, YY
Citation: A. Agresti et Yy. Min, On small-sample confidence intervals for parameters in discrete distributions, BIOMETRICS, 57(3), 2001, pp. 963-971
Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures - Reply
Authors: Agresti, A
Citation: A. Agresti, Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures - Reply, AM STATISTN, 55(3), 2001, pp. 261-261
Agresti, A., and Caffo, B. (2000), "Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures," The American Statistician, 54, 280-288: Commentby Greenland and Reply
Authors: Agresti, A
Citation: A. Agresti, Agresti, A., and Caffo, B. (2000), "Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures," The American Statistician, 54, 280-288: Commentby Greenland and Reply, AM STATISTN, 55(2), 2001, pp. 172-173
Hierarchical Bayesian analysis of binary matched pairs data
Authors: Ghosh, M Chen, MH Ghosh, A Agresti, A
Citation: M. Ghosh et al., Hierarchical Bayesian analysis of binary matched pairs data, STAT SINICA, 10(2), 2000, pp. 647-657
Strategies for comparing treatments on a binary response with multi-centredata
Authors: Agresti, A Hartzel, J
Citation: A. Agresti et J. Hartzel, Strategies for comparing treatments on a binary response with multi-centredata, STAT MED, 19(8), 2000, pp. 1115-1139
Summarizing the predictive power of a generalized linear model
Authors: Zheng, BY Agresti, A
Citation: By. Zheng et A. Agresti, Summarizing the predictive power of a generalized linear model, STAT MED, 19(13), 2000, pp. 1771-1781
A theoretical study on reaction pathways to carbanions
Authors: Alagona, G Ghio, C Agresti, A
Citation: G. Alagona et al., A theoretical study on reaction pathways to carbanions, COMPUT CHEM, 24(3-4), 2000, pp. 311-324
Random-effects modeling of categorical response data
Authors: Agresti, A Booth, JG Hobert, JP Caffo, B
Citation: A. Agresti et al., Random-effects modeling of categorical response data, SOCIOL MET, 30, 2000, pp. 27-80
Random effects modeling of multiple binomial responses using the multivariate binomial logit-normal distribution
Authors: Coull, BA Agresti, A
Citation: Ba. Coull et A. Agresti, Random effects modeling of multiple binomial responses using the multivariate binomial logit-normal distribution, BIOMETRICS, 56(1), 2000, pp. 73-80
Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures
Authors: Agresti, A Caffo, B
Citation: A. Agresti et B. Caffo, Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures, AM STATISTN, 54(4), 2000, pp. 280-288
Agresti, A., and Coull, B. A. (1998), "Approximate is better than 'exact' for interval estimation of binomial proportions," The American Statistician, 52, 119-126: Comment by Rindskopf and reply - Response
Authors: Agresti, A Coull, B
Citation: A. Agresti et B. Coull, Agresti, A., and Coull, B. A. (1998), "Approximate is better than 'exact' for interval estimation of binomial proportions," The American Statistician, 52, 119-126: Comment by Rindskopf and reply - Response, AM STATISTN, 54(1), 2000, pp. 88-88
Challenges for categorical data analysis in the twenty-first century
Authors: Agresti, A
Citation: A. Agresti, Challenges for categorical data analysis in the twenty-first century, STAT TEXT M, 161, 2000, pp. 1-19
Analysis of gamma 4 germline transcription in human B cells
Authors: Agresti, A Vercelli, D
Citation: A. Agresti et D. Vercelli, Analysis of gamma 4 germline transcription in human B cells, INT A AL IM, 118(2-4), 1999, pp. 279-281
An uncommon endotracheal finding
Authors: Vaylet, F Agresti, A Martinez, M Guigay, J Jancovici, R L'Her, P
Citation: F. Vaylet et al., An uncommon endotracheal finding, REV MAL RES, 16(2), 1999, pp. 222-223
Modelling ordered categorical data: Recent advances and future challenges
Authors: Agresti, A
Citation: A. Agresti, Modelling ordered categorical data: Recent advances and future challenges, STAT MED, 18(17-18), 1999, pp. 2191-2207
Modeling a categorical variable allowing arbitrarily many category choices
Authors: Agresti, A Liu, IM
Citation: A. Agresti et Im. Liu, Modeling a categorical variable allowing arbitrarily many category choices, BIOMETRICS, 55(3), 1999, pp. 936-943
On logit confidence intervals for the odds ratio with small samples
Authors: Agresti, A
Citation: A. Agresti, On logit confidence intervals for the odds ratio with small samples, BIOMETRICS, 55(2), 1999, pp. 597-602
The use of mixed logit models to reflect heterogeneity in capture-recapture studies
Authors: Coull, BA Agresti, A
Citation: Ba. Coull et A. Agresti, The use of mixed logit models to reflect heterogeneity in capture-recapture studies, BIOMETRICS, 55(1), 1999, pp. 294-301
Approximately exact inference for the common odds ratio in several 2 x 2 tables - Comment
Authors: Agresti, A
Citation: A. Agresti, Approximately exact inference for the common odds ratio in several 2 x 2 tables - Comment, J AM STAT A, 93(444), 1998, pp. 1307-1310
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