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Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials
2013
Neurology
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binomial time to event; TTFR 5 time to first relapse; ZINB 5 zero-inflated negative binomial; ZIP 5 zero-inflated Poisson. ...
Methods: Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled ...
, iii) the zero-inflated Poisson (ZIP) model, and iv) the zero-inflated NB (ZINB) model. ...
doi:10.1212/wnl.0b013e3182a6cb9b
pmid:23966255
pmcid:PMC3795606
fatcat:7x2tir5awrcdnhczpetlkokaoq
Migraine day frequency in migraine prevention: longitudinal modelling approaches
2019
BMC Medical Research Methodology
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Using these cohort-level endpoints in economic models, accounting for variation among patients is challenging. ...
Health economic models are critical tools to inform reimbursement agencies on health care interventions. ...
Placebo modelling data: MMDs of the EM study (a) and the CM study (b) negative binomial regression, beta binomial regression and zero-inflated negative binomial regression. ...
doi:10.1186/s12874-019-0664-5
pmid:30674285
pmcid:PMC6343253
fatcat:cnjxazdvgngwzml5ueu75rltgi
Zero adjusted models with applications to analysing helminths count data
2014
BMC Research Notes
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The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study. ...
Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle ...
For example, if the study design leads to count endpoints with both structural and sample zeros then generally the zero-inflated modeling framework is more appropriate, while in contrast, if the endpoint ...
doi:10.1186/1756-0500-7-856
pmid:25430726
pmcid:PMC4289350
fatcat:gyirfxk25farln7yt5havexajq
Ecotoxicology is not normal
2015
Environmental science and pollution research international
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tions from counts by binomial GLMs. These methods should become standard in ecotoxicology. ...
Methods to deal with overdispersed binomial data are for example quasi methods (see above) or Generalized Linear Mixed models (GLMM). ...
Simulations
Count data For detecting a general treatment effect, GLM nb and GLM p showed inflated Type I error rates, whereas KW was conservative at low sample sizes. ...
doi:10.1007/s11356-015-4579-3
pmid:25953608
fatcat:ckcpw7ejyzdfdmtllnvnaiolfe
Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint
2012
BMC Medical Research Methodology
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In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. ...
Methods: We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over-and under-dispersion is considered. ...
Variability of mean logarithmic score LS (r) for true negative binomial (NB) compared with arcsinh, (zero-inflated) Poisson and zero-inflated NB model (r = 1, . . . , 100 iterations per scenario). ...
doi:10.1186/1471-2288-12-137
pmid:22962944
pmcid:PMC3554595
fatcat:htvioxhcibefba6ogi6af3nf2e
Group sequential designs for negative binomial outcomes
2018
Statistical Methods in Medical Research
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2017 pre-print arXiv:1707.04612v1 fatcat:ea6644akwvcndh22kbroammxfmOther Versions
by negative binomial distributions. ...
, the number of relapses in multiple sclerosis, the number of hospitalizations in heart failure, and the number of exacerbations in asthma or in chronic obstructive pulmonary disease (COPD) are often modeled ...
In this manuscript we focus on group sequential designs with recurrent events modeled by a negative binomial distribution which is commonly considered to model endpoints in clinical trials in multiple ...
doi:10.1177/0962280218773115
pmid:29770729
fatcat:5c4zg2a27zhnlhfpnd7vpuxtli
Performance of Some Correlation Coefficients When Applied to Zero-Clustered Data
2007
Journal of Modern Applied Statistical Methods
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Methodology I Generating Samples of Correlated Zero-Clustered Data Two different models were used to generate zero-clustered data for the simulation study -the binomial-lognormal model and the truncated ...
simulation study of the performance of the Pearson and Spearman correlation coefficients, when applied to zero-clustered data generated using the binomial-lognormal model. -------------------- ------- ...
doi:10.22237/jmasm/1193890560
fatcat:xhdzyfoanvfvja5xi6bejaeiam
Analysis of peginterferon β-1a exposure and Gd-enhanced lesion or T2 lesion response in relapsing-remitting multiple sclerosis patients
2016
Journal of Pharmacokinetics and Pharmacodynamics
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Several longitudinal count models, including marginal, mixed effect, and mixture models, were compared to explore the relationship between AUC ss and Gd? lesion count (or T2 lesion count). ...
Steady state 4-week AUC (AUCss) was derived for each individual based on sparse pharmacokinetic (PK) sample and a population PK model. ...
lesion count over 48 months in nine MS patients; these models incorporated different distribution families (Poisson, ZIP, generalized Poisson, negative binomial, and zero-inflated negative binomial) with ...
doi:10.1007/s10928-016-9477-x
pmid:27299457
pmcid:PMC4954841
fatcat:rzlpvwuqlvffxog2zaygecax5i
Bayesian Gamma-Negative Binomial Modeling of Single-Cell RNA Sequencing Data
[article]
2019
arXiv
pre-print
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Results: In this paper, we propose a fully generative hierarchical gamma-negative binomial (hGNB) model of scRNA-seq data, obviating the need for explicitly modeling zero inflation. ...
The unique analytic challenge is to appropriately model highly over-dispersed scRNA-seq count data with prevalent dropouts (zero counts), making zero-inflated dimensionality reduction techniques popular ...
Zeroinflated negative binomial-based wanted variation extraction (ZINB-WaVE) [9] directly models the scRNAseq counts using a zero-inflated negative binomial distribution, while accounting for both gene-and ...
arXiv:1908.00650v1
fatcat:mj7cwzekizdo3meguy3quyqzuu
A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants
2014
Ecology and Evolution
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The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. ...
This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. ...
The simulation model described in this paper can be used to generate data for various endpoints having Figure 6 . ...
doi:10.1002/ece3.1019
pmid:24834325
pmcid:PMC4020688
fatcat:psf7et6f3vdf7imktyoq7xsrdi
Meta analysis of binary data with excessive zeros in two-arm trials
2019
Journal of Statistical Distributions and Applications
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A zero inflated binomial model with excessive zero parameters were used to account for excessive zeros in treatment and control arms. ...
Results from the data analysis and the model selection also indicate that the proposed Bayesian method, while accounting for zero events, adjusts for excessive zeros and provides better fit to the data ...
Also note that Binomial and zero inflated Binomial models identify more heterogeneous study effects than DerSimonian-Laird random effects model. ...
doi:10.1186/s40488-019-0099-x
fatcat:l3ke5jo6kncepoqx5s5lx2o37q
An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data
2017
Nature Communications
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model zero inflation and overdispersion. ...
HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts-for example, distance-dependent random polymer ligation and GC content and mappability bias-and ...
This model is sometimes called a hurdle negative binomial model. ...
doi:10.1038/ncomms15454
pmid:28513628
pmcid:PMC5442359
fatcat:kyesvtqxrza3leckhzo5npbvaq
Bayesian gamma-negative binomial modeling of single-cell RNA sequencing data
2020
BMC Genomics
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The file type is application/pdf.
In this paper, we propose a fully generative hierarchical gamma-negative binomial (hGNB) model of scRNA-seq data, obviating the need for explicitly modeling zero inflation. ...
The unique analytic challenge is to appropriately model highly over-dispersed scRNA-seq count data with prevalent dropouts (zero counts), making zero-inflated dimensionality reduction techniques popular ...
Zero-inflated negative binomialbased wanted variation extraction (ZINB-WaVE) [9] directly models the scRNA-seq counts using a zeroinflated negative binomial distribution, while accounting for both gene-and ...
doi:10.1186/s12864-020-06938-8
pmid:32900358
pmcid:PMC7487589
fatcat:o2yi4lromvabhnjalal5zrllde
Peritraumatic tonic immobility is associated with PTSD symptom severity in Brazilian police officers: a prospective study
2014
Revista Brasileira de Psiquiatria
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Results: Employing a zero-inflated negative binomial regression model, we found that each additional point in the TIS was associated with a 9% increment in PCL-C mean scores (RM = 1.09), whereas for PRS ...
Figure 3 3 Fitting for Poisson (PRN), negative binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) regression models. ...
zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB). 29 The ZINB model was chosen because the proportion of cases with no symptoms in the PCL scale was excessive and data were overdispersed ...
doi:10.1590/1516-4446-2013-1267
pmid:25466958
fatcat:dwjmeckscfgf5fkbh4kckkpguq
Page 7018 of Mathematical Reviews Vol. , Issue 97K
[page]
1997
Mathematical Reviews
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
We derive interesting and useful formulae for the binomial, Poisson, negative binomial and gamma populations.” ...
In this paper the authors consider the most general case of additive models with bounded errors and show that every suf- ficiently regular UMVU estimator is deterministic. ...
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