Modeling and Simulation of Count Data
暂无分享,去创建一个
[1] D R Mould,et al. Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development: Part 3—Introduction to Pharmacodynamic Modeling Methods , 2014, CPT: pharmacometrics & systems pharmacology.
[2] Nan M. Laird,et al. Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques , 1981 .
[3] M. Karlsson,et al. Transient Lower Esophageal Sphincter Relaxation Pharmacokinetic-Pharmacodynamic Modeling: Count Model and Repeated Time-To-Event Model , 2011, Journal of Pharmacology and Experimental Therapeutics.
[4] Siméon-Denis Poisson. Recherches sur la probabilité des jugements en matière criminelle et en matiére civile, précédées des règles générales du calcul des probabilités , 1837 .
[5] K Ito,et al. Application of ggplot2 to Pharmacometric Graphics , 2013, CPT: pharmacometrics & systems pharmacology.
[6] L. Benet,et al. Two-compartment model for a drug and its metabolite: application to acetylsalicylic acid pharmacokinetics. , 1970, Journal of pharmaceutical sciences.
[7] Mats O. Karlsson,et al. Analysis of exposure–response of CI-945 in patients with epilepsy: application of novel mixed hidden Markov modeling methodology , 2012, Journal of Pharmacokinetics and Pharmacodynamics.
[8] Abraham De Moivre. De mensura sortis, seu, de probabilitate eventuum in ludis a casu fortuito pendentibus , 1710, Philosophical Transactions of the Royal Society of London.
[9] Paul G. Hoel,et al. On Indices of Dispersion , 1943 .
[10] Lewis B. Sheiner,et al. Evaluation of methods for estimating population pharmacokinetic parameters. I. Michaelis-menten model: Routine clinical pharmacokinetic data , 1980, Journal of Pharmacokinetics and Biopharmaceutics.
[11] E. Mulvey,et al. Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. , 1995, Psychological bulletin.
[12] P. Bonate,et al. Conditional modeling of antibody titers using a zero-inflated poisson random effects model: application to Fabrazyme® , 2009, Journal of Pharmacokinetics and Pharmacodynamics.
[13] R J Keizer,et al. Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose , 2013, CPT: pharmacometrics & systems pharmacology.
[14] Mats O. Karlsson,et al. Three new residual error models for population PK/PD analyses , 1995, Journal of Pharmacokinetics and Biopharmaceutics.
[15] D. Pierce,et al. Residuals in Generalized Linear Models , 1986 .
[16] Sabine Himmel,et al. Exploring Data Tables, Trends, and Shapes , 2007 .
[17] R. Winkelmann,et al. Count data models for demographic data. , 1994, Mathematical population studies.
[18] Panagiotis Besbeas,et al. An empirical model for underdispersed count data , 2004 .
[19] Mats O. Karlsson,et al. Modelling overdispersion and Markovian features in count data , 2009, Journal of Pharmacokinetics and Pharmacodynamics.
[20] L B Sheiner,et al. The population approach to pharmacokinetic data analysis: rationale and standard data analysis methods. , 1984, Drug metabolism reviews.
[21] Stephen Duffull,et al. Modeling and Simulation for Clinical Trial Design Involving a Categorical Response: A Phase II Case Study with Naratriptan , 2001, Pharmaceutical Research.
[22] Michel Tod,et al. Pharmacodynamic Models for Discrete Data , 2012, Clinical Pharmacokinetics.
[23] Srinivas Reddy Geedipally,et al. Over- and Under-Dispersed Count Data: Comparing Conway-Maxwell-Poisson and Double-Poisson Distributions , 2012 .
[24] B. Selby,et al. The index of dispersion as a test statistic , 1965 .
[25] Taylor Francis Online,et al. The American statistician , 1947 .
[26] Marc Lavielle,et al. Performance in population models for count data, part II: A new SAEM algorithm , 2009, Journal of Pharmacokinetics and Pharmacodynamics.
[27] P. Consul,et al. A Generalization of the Poisson Distribution , 1973 .
[28] M O Karlsson,et al. Likert Pain Score Modeling: A Markov Integer Model and an Autoregressive Continuous Model , 2012, Clinical pharmacology and therapeutics.
[29] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[30] Marc R Gastonguay,et al. Pharmacometrics: A Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings , 2008, Journal of clinical pharmacology.
[31] J. T. Wulu,et al. Regression analysis of count data , 2002 .
[32] T. Holford. The analysis of rates and of survivorship using log-linear models. , 1980, Biometrics.
[33] S. West,et al. The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives , 2009, Journal of personality assessment.
[34] Henrik Madsen,et al. Stochastic Differential Equations in NONMEM®: Implementation, Application, and Comparison with Ordinary Differential Equations , 2005, Pharmaceutical Research.
[35] David C. Hoaglin,et al. A Poissonness Plot , 1980 .
[36] P. C. Consul,et al. The generalized poisson distribution when the sample mean is larger than the sample variance , 1985 .
[37] Mats O. Karlsson,et al. Performance in population models for count data, part I: maximum likelihood approximations , 2009, Journal of Pharmacokinetics and Pharmacodynamics.
[38] S. Zeger,et al. Markov regression models for time series: a quasi-likelihood approach. , 1988, Biometrics.
[39] Leon Aarons,et al. Sample Size Calculations for Population Pharmacodynamic Experiments Involving Repeated Dichotomous Observations , 2007, Journal of biopharmaceutical statistics.
[40] Lewis B. Sheiner,et al. A Population Pharmacokinetic–Pharmacodynamic Analysis of Repeated Measures Time-to-Event Pharmacodynamic Responses: The Antiemetic Effect of Ondansetron , 1999, Journal of Pharmacokinetics and Biopharmaceutics.
[41] K. Land,et al. A Comparison of Poisson, Negative Binomial, and Semiparametric Mixed Poisson Regression Models , 1996 .
[42] Lewis B. Sheiner,et al. The Need for Mixed-Effects Modeling with Population Dichotomous Data , 2001, Journal of Pharmacokinetics and Pharmacodynamics.
[43] M O Karlsson,et al. Approaches to Simultaneous Analysis of Frequency and Severity of Symptoms , 2010, Clinical pharmacology and therapeutics.
[44] N. Balakrishnan,et al. On the Compound Generalized Poisson Distributions , 1994 .
[45] D R Mould,et al. Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development—Part 2: Introduction to Pharmacokinetic Modeling Methods , 2013, CPT: pharmacometrics & systems pharmacology.
[46] P. E. Kopp,et al. Superspreading and the effect of individual variation on disease emergence , 2005, Nature.
[47] N. Singpurwalla. The Hazard Potential , 2006 .
[48] L B Sheiner,et al. Quantitative characterization of therapeutic index: Application of mixed‐effects modeling to evaluate oxybutynin dose–efficacy and dose–side effect relationships , 1999, Clinical pharmacology and therapeutics.
[49] F. Mosteller,et al. Exploring Data Tables, Trends and Shapes. , 1988 .
[50] D R Mould,et al. Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development , 2012, CPT: pharmacometrics & systems pharmacology.
[51] Srinivas Reddy Geedipally,et al. Evaluating the double Poisson generalized linear model. , 2013, Accident; analysis and prevention.
[52] J. Box. R.A. Fisher and the Design of Experiments, 1922–1926 , 1980 .
[53] Andrew C. Hooker,et al. Optimal design in nonlinear mixed effects models with discrete type data including Categorical, Count, Dropout and Markov models , 2011 .
[55] J. Nadstawek,et al. Less nausea, emesis, and constipation comparing hydromorphone and morphine? A prospective open-labeled investigation on cancer pain , 2008, Supportive Care in Cancer.
[56] Evaluation of Mixture Modeling with Count Data Using NONMEM , 2003, Journal of Pharmacokinetics and Pharmacodynamics.
[57] Pravin K. Trivedi,et al. Regression Analysis of Count Data , 1998 .
[58] B. Efron. Double Exponential Families and Their Use in Generalized Linear Regression , 1986 .
[59] M. Danhof,et al. Anticonvulsant drugs differentially suppress individual ictal signs: a pharmacokinetic/pharmacodynamic analysis in the cortical stimulation model in the rat. , 2003, Behavioral neuroscience.
[60] Mats O Karlsson,et al. Modeling Longitudinal Daily Seizure Frequency Data From Pregabalin Add‐On Treatment , 2012, Journal of clinical pharmacology.
[61] G. King,et al. Variance Specification in Event Count Models: From Restrictive Assumptions to a Generalized Estimator , 1989 .
[62] N. Holford. A Time to Event Tutorial for Pharmacometricians , 2013, CPT: pharmacometrics & systems pharmacology.
[63] E. Niclas Jonsson,et al. PsN-Toolkit - A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM , 2005, Comput. Methods Programs Biomed..