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Begg, M. D., & Lagakos, S. W. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10594307 · Cited by 37
Wu, H., & Wu, L. (2002) · Statistics in Medicine · doi:10.1002/sim.1015 · Cited by 32
A family of fractional age assumptions
Jones, B. L., & Mereu, J. A. (2000) · Insurance Mathematics and Economics · doi:10.1016/s0167-6687(00)00052-4 · Cited by 32
A Bayesian group sequential design for a multiple arm randomized clinical trial
Rosner, G. L., & Berry, D. A. (1995) · Statistics in Medicine · doi:10.1002/sim.4780140405 · Cited by 32
Corrected maximum likelihood estimators in heteroscedastic symmetric nonlinear models
Cysneiros, F. J. A., Cordeiro, G. M., & Cysneiros, A. H. M. A. (2009) · Journal of Statistical Computation and Simulation · doi:10.1080/00949650802706420 · Cited by 32
Barndorff-Nielsen, O. E. (2014) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat00970 · Cited by 32
Bagheri, A., & Abolhasani, A. (2014) · Korean Journal of Chemical Engineering · doi:10.1007/s11814-014-0232-y · Cited by 31
Quality of Analytical Measurements: Univariate Regression
Ortiz, M. C., Sánchez, M. S., & Sarabia, L. A. (2009) · Elsevier eBooks · doi:10.1016/b978-044452701-1.00091-0 · Cited by 36
The Information in Aggregate Data
Steel, D. G., Beh, E. J., & Chambers, R. L. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511510595.004 · Cited by 31
Inference for Sichel's Compound Poisson Distribution
Atkinson, A. C., & Yeh, L. (1982) · Journal of the American Statistical Association · doi:10.1080/01621459.1982.10477779 · Cited by 31
Geometric Understanding of Likelihood Ratio Statistics
Fan, J., Hung, H.-N., & Wong, W.-H. (2000) · Journal of the American Statistical Association · doi:10.1080/01621459.2000.10474275 · Cited by 31
An analysis of the controversy over classical one-sided tests
Freedman, L. S. (2008) · Clinical Trials · doi:10.1177/1740774508098590 · Cited by 32
Model parameter estimation bias induced by earthquake magnitude cut-off
Harte, D. S. (2015) · Geophysical Journal International · doi:10.1093/gji/ggv524 · Cited by 31
Measuring the Effectiveness of Readability for Mobile Robot Locomotion
Carton, D., Olszowy, W., & Wollherr, D. (2016) · International Journal of Social Robotics · doi:10.1007/s12369-016-0358-7 · Cited by 31
Efficient profile-likelihood confidence intervals for capture-recapture models
Giménez, O., Choquet, R., Lamor, L., Scofield, R. P., Fletcher, D., Lebreton, J., & Pradel, R. (2005) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1198/108571105x46462 · Cited by 30
Dillbeck, M. C. (1990) · Social Indicators Research · doi:10.1007/bf00303834 · Cited by 31
Pattern Recognition and Density Estimation under the General i.i.d. Assumption
Nouretdinov, I., Vovk, V., Vyugin, M. V., et al. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44581-1_22 · Cited by 31
Listronotus bonariensis(Coleoptera: Curculionidae) flight in Canterbury, New Zealand
Goldson, S. L., Proffitt, J. R., & Baird, D. (1999) · Bulletin of Entomological Research · doi:10.1017/s0007485399000553 · Cited by 31
Xu, R., & Li, X. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg155 · Cited by 31
Asymptotic inference for an ising lattice. II
Pickard, D. K. (1977) · Advances in Applied Probability · doi:10.2307/1426110 · Cited by 31
Topics in advanced time series analysis
Solo, V. (1986) · Lecture notes in mathematics · doi:10.1007/bfb0075874 · Cited by 31
Measurement error in time-series analysis: a simulation study comparing modelled and monitored data
Butland, B. K., Armstrong, B., Atkinson, R. W., et al. (2013) · BMC Medical Research Methodology · doi:10.1186/1471-2288-13-136 · Cited by 30
Generalized inverse Lindley distribution with application to Danish fire insurance data
Asgharzadeh, A., Nadarajah, S., & Sharafi, F. (2016) · Communication in Statistics- Theory and Methods · doi:10.1080/03610926.2015.1096394 · Cited by 30
Changes in the Risk of Extreme Climate Events over East Asia at Different Global Warming Levels
Zhang, J., & Wang, F. (2019) · Water · doi:10.3390/w11122535 · Cited by 29
Generalized linear mixed joint model for longitudinal and survival outcomes
Viviani, S., Alfò, M., & Rizopoulos, D. (2013) · Statistics and Computing · doi:10.1007/s11222-013-9378-4 · Cited by 30
Hypothesis testing in an errors‐in‐variables model with heteroscedastic measurement errors
de Castro, M., Galea, M., & Bolfarine, H. (2008) · Statistics in Medicine · doi:10.1002/sim.3343 · Cited by 30
Bayeswatch: an overview of Bayesian statistics
Austin, P. C., Brunner, L. J., & SM, J. E. H. M. (2002) · Journal of Evaluation in Clinical Practice · doi:10.1046/j.1365-2753.2002.00338.x · Cited by 30
Misspecification tests based on quantile residuals
Kalliovirta, L. (2012) · Econometrics Journal · doi:10.1111/j.1368-423x.2011.00364.x · Cited by 29
Comparative kinetics of embryo development
ZONNEVELD, C., & Kooijman, S. A. L. M. (1993) · Bulletin of Mathematical Biology · doi:10.1007/bf02460653 · Cited by 30
Dummy variables vs. category-wise models
Holgersson, H. E. T., Nordström, L., & Öner, Ö. (2013) · Journal of Applied Statistics · doi:10.1080/02664763.2013.838665 · Cited by 30
Broët, P., Kuznetsov, V. A., Bergh, J. C. S., Liu, E. T., & Miller, L. D. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl110 · Cited by 29
Voles and lemmings: chaos and uncertainty in fluctuating populations
Falck, W., Bjørnstad, O. N., & Stenseth, N. C. (1995) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1995.0218 · Cited by 30
GENETIC epidemiology: A review of the statistical basis
Thompson, E. A. (1986) · Statistics in Medicine · doi:10.1002/sim.4780050402 · Cited by 30
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Shaw, R. G. (1992) · Evolution · doi:10.1111/j.1558-5646.1992.tb01185.x · Cited by 30
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Gauvreau, K., & Pagano, M. (1997) · Biometrical Journal · doi:10.1002/bimj.4710390306 · Cited by 29
Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses
Silva, L. D. C. E., Wang, S., & Zeng, Z. (2012) · BMC Genetics · doi:10.1186/1471-2156-13-67 · Cited by 29
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Leão, J., Leiva, V., Saulo, H., et al. (2018) · Brazilian Journal of Probability and Statistics · doi:10.1214/17-bjps360 · Cited by 29
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Hallin, M., & Ley, C. (2014) · Bernoulli · doi:10.3150/13-bej528 · Cited by 29
The impact of taxes and transfer payments on the distribution of income: A parametric comparison
Dastrup, S. R., Hartshorn, R., & McDonald, J. B. (2007) · The Journal of Economic Inequality · doi:10.1007/s10888-006-9039-3 · Cited by 29
Extending permutation conditional inference to unconditional ones
Pesarin, F. (2002) · Statistical Methods & Applications · doi:10.1007/bf02511484 · Cited by 29
Shelf life determination using sensory evaluation scores: A general Weibull modeling approach
Freitas, M. A., & Costa, J. C. B. (2006) · Computers & Industrial Engineering · doi:10.1016/j.cie.2006.04.005 · Cited by 29
Generalized genetic association study with samples of related individuals
Feng, Z. Z., Wong, W. W. L., Gao, X., & Schenkel, F. S. (2011) · The Annals of Applied Statistics · doi:10.1214/11-aoas465 · Cited by 28
Reliability estimation based on operational data of manufacturing systems
Li, L., & Ni, J. (2008) · Quality and Reliability Engineering International · doi:10.1002/qre.959 · Cited by 29
Stressful life events and cognitive functioning in late life
Grimby, A., & Berg, S. (1995) · Aging Clinical and Experimental Research · doi:10.1007/bf03324290 · Cited by 29
In Defence of Score Intervals for Proportions and their Differences
Newcombe, R. G., & Nurminen, M. M. (2011) · Communication in Statistics- Theory and Methods · doi:10.1080/03610920903576580 · Cited by 29
Bayesian design strategies for synthetic biology
Barnes, C. P., Silk, D., & Stumpf, M. P. H. (2011) · Interface Focus · doi:10.1098/rsfs.2011.0056 · Cited by 28
Sand, S., von Rosen, D., & Filipsson, A. F. (2003) · Risk Analysis · doi:10.1111/1539-6924.00381 · Cited by 29
Use of a Pharmacokinetic/Pharmacodynamic Model to Design an Optimal Dose Input Profile
Park, K., Verotta, D., Gupta, S., et al. (1998) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1023/a:1021068202606 · Cited by 29
Analysis of Two-Way Layout of Count Data Involving Multiple Counts in Each Cell
Paul, S. R., & Banerjee, T. (1998) · Journal of the American Statistical Association · doi:10.1080/01621459.1998.10473802 · Cited by 29
Use of Cohort Information in the Design and Analysis of Case‐Control Studies
Langholz, B. M. (2007) · Scandinavian Journal of Statistics · doi:10.1111/j.1467-9469.2006.00548.x · Cited by 29
Estimation and Testing for a Markov Model of Reinforcement
Allison, P. D. (1980) · Sociological Methods & Research · doi:10.1177/004912418000800405 · Cited by 29
Fast evaluation of the likelihood of an HMM: ion channel currents with filtering and colored noise
Fredkin, D. R., & Rice, J. A. (2001) · IEEE Transactions on Signal Processing · doi:10.1109/78.905892 · Cited by 29
The interpretation of maximum‐likelihood estimation
Sprott, D. A., & Viveros‐Aguilera, R. (1984) · Canadian Journal of Statistics · doi:10.2307/3314722 · Cited by 26
Bootstrapping in least absolute value regression: an application to hypothesis testing
Dielman, T. E., & Pfaffenberger, R. C. (1988) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918808812699 · Cited by 29
Model-Averaged Profile Likelihood Intervals
Fletcher, D., & Turek, D. (2011) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-011-0064-8 · Cited by 26
On internally corrected and symmetrized kernel estimators for nonparametric regression
Linton, O. B., & Jacho‐Chávez, D. T. (2009) · Test · doi:10.1007/s11749-009-0145-y · Cited by 28
Berrar, D. (2016) · Machine Learning · doi:10.1007/s10994-016-5612-6 · Cited by 29
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Patent Examination Quality and Litigation: Is There a Link?
Marco, A. C., & Miller, R. D. (2019) · International Journal of the Economics of Business · doi:10.1080/13571516.2018.1553286 · Cited by 28
Fung, T., & Keenan, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0085925 · Cited by 28
On the consequences of model misspecification in logistic regression.
Begg, M. D., & Lagakos, S. W. (1990) · Environmental Health Perspectives · doi:10.1289/ehp.908769 · Cited by 28
Generation Means Analysis Using Mixed Models
Piepho, H., & Möhring, J. (2010) · Crop Science · doi:10.2135/cropsci2010.02.0093 · Cited by 28
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Nadarajah, S. (2011) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2011.04.018 · Cited by 24
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Roy, S., Banerjee, T., & Maiti, T. (2004) · Statistics in Medicine · doi:10.1002/sim.1886 · Cited by 28
Logistic regression of family data from retrospective study designs
Whittemore, A. S., & Halpern, J. (2003) · Genetic Epidemiology · doi:10.1002/gepi.10267 · Cited by 28
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Tegtmeier, C., Stryhn, H., Uttenthal, Å., et al. (2000) · Acta veterinaria Scandinavica · doi:10.1186/bf03549624 · Cited by 28
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Gustafson, P., & Greenland, S. (2006) · Biometrics · doi:10.1111/j.1541-0420.2005.00510.x · Cited by 28
Neutron induced soft errors in CMOS memories under reduced bias
Hazucha, P., Johansson, K. E., & Svensson, C. (1998) · IEEE Transactions on Nuclear Science · doi:10.1109/23.736548 · Cited by 28
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Pinheiro, J. C. (2014) · Wiley eBooks · doi:10.1002/9781118445112.stat05514 · Cited by 27
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Vía, J., Palomar, D. P., & Vielva, L. (2010) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2101067 · Cited by 27
Sundberg, R. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108604574.010 · Cited by 28
High Dimensional Classification with Bayesian Neural Networks and Dirichlet Diffusion Trees
Neal, R. M., & Zhang, J. (2008) · Studies in fuzziness and soft computing · doi:10.1007/978-3-540-35488-8_11 · Cited by 29
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Lundgren, M., Emilson, C. G., Österberg, T., et al. (1997) · Acta Odontologica Scandinavica · doi:10.3109/00016359709114965 · Cited by 27
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Sinharay, S. (2020) · Applied Psychological Measurement · doi:10.1177/0146621620909893 · Cited by 28
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Klyushin, D. A., & Petunin, Y. I. (2003) · Ukrainian Mathematical Journal · doi:10.1023/a:1025495727612 · Cited by 27
How many victims will a pitfall make?
Jansen, M. J. W., & Metz, J. A. J. (1979) · Acta Biotheoretica · doi:10.1007/bf00046807 · Cited by 27
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Gibbons, R. D. (2000) · Health Services and Outcomes Research Methodology · doi:10.1023/a:1010018505011 · Cited by 27
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Garthright, W. E. (1993) · Biometrical Journal · doi:10.1002/bimj.4710350306 · Cited by 27
Quantile dispersion graphs for evaluating and comparing designs for logistic regression models
Robinson, K. S., & Khuri, A. I. (2003) · Computational Statistics & Data Analysis · doi:10.1016/s0167-9473(02)00182-2 · Cited by 27
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Best, D. J., & Rayner, J. C. W. (1987) · Technometrics · doi:10.1080/00401706.1987.10488211 · Cited by 27
Classes of Similar Regions and Their Power Properties for Some Econometric Testing Problems
Hillier, G. (1987) · Econometric Theory · doi:10.1017/s0266466600004114 · Cited by 26
Statistical Models for the Analysis of Volatile Organic Compounds in Waste Disposal Sites
Gibbons, R. D. (1987) · Ground Water · doi:10.1111/j.1745-6584.1987.tb02887.x · Cited by 27
The analysis of prospective studies of disease aetiology
Clayton, D. G. (1982) · Communication in Statistics- Theory and Methods · doi:10.1080/03610928208828377 · Cited by 27
Sensitivity of Fisher's exact test to minor perturbations in 2 × 2 contingency tables
Dupont, W. D. (1986) · Statistics in Medicine · doi:10.1002/sim.4780050610 · Cited by 27
Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process ModelsPreprint
Baddeley, A. J., Rubak, E., & Møller, J. (2016) · Cited by 27
The Generalized Likelihood Ratio Test and the Sparse Representations Approach
Fuchs, J. J. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13681-8_29 · Cited by 26
Reverse Engineering Under Uncertainty
Kirk, P., Silk, D., & Stumpf, M. P. H. (2015) · Studies in mechanobiology, tissue engineering and biomaterials · doi:10.1007/978-3-319-21296-8_2 · Cited by 25
A beta partial least squares regression model: Diagnostics and application to mining industry data
Huerta, M., Leiva, V., Lillo, C., & Rodríguez, M. (2017) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.2278 · Cited by 24
Rubin, M. (2019) · Synthese · doi:10.1007/s11229-019-02433-0 · Cited by 26
Duan, H., Yu, X., Kai, S., et al. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.1049765 · Cited by 26
Smith, E. P., & Marx, B. D. (1990) · Environmetrics · doi:10.1002/env.3170010107 · Cited by 26
Chowdhary, H., & Singh, V. P. (2010) · Water Resources Research · doi:10.1029/2009wr008490 · Cited by 26
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Baggenstoss, P. M. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2419189 · Cited by 26
Transformations to Linearity in Binary Regression
Whittemore, A. S. (1983) · SIAM Journal on Applied Mathematics · doi:10.1137/0143048 · Cited by 26
Edge Exclusion Tests for Graphical Gaussian Models
Smith, P. W. F., & Whittaker, J. (1998) · Springer eBooks · doi:10.1007/978-94-011-5014-9_21 · Cited by 26
Metadata
- Authors
- Cox, D. R., & Hinkley, D. V.
- ORCID
- Cox, D. R.
- Venue
- Springer eBooks
- Publisher
- Springer US
- Published
- 1974
- OpenAlex
- W4240874411
- Cited by
- 3,089
- References
- 0
- Citations by year
- 2026: 29 · 2025: 43 · 2024: 32 · 2023: 50 · 2022: 62 · 2021: 60 · 2020: 64 · 2019: 85 · 2018: 89 · 2017: 90 · 2016: 79 · 2015: 76 · 2014: 153 · 2013: 86 · 2012: 101
- FWCI
- 7.91
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- mathematical statistics
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