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Do not log-transform count data

Robert O'Hara, Johan Kotze
2010 Nature Precedings  
The Poisson and negative binomial models consistently performed well, with little bias.  ...  Simulating data from a negative binomial distribution, we compared the outcome of fitting models that were transformed in various ways (log, square-root) with results from fitting models using Poisson  ...  Acknowledgments The order of the authors was determined by the result of the South Africa  ... 
doi:10.1038/npre.2010.4136.1 fatcat:tcvfxoqegbd47iceg7j7nyz3nu


Craig A. Stow, Kenneth H. Reckhow, Song S. Qian
2006 Ecology  
For the normal linear model, fit under a log-transformation, correction factors are available to reduce this bias, but these factors may not be generally applicable to all model forms or other transformations  ...  We demonstrate that this problem is handled in a straightforward manner using a Bayesian approach, which is general for linear and nonlinear models and other transformations and model error structures.  ...  ACKNOWLEDGMENTS This work was partially supported by EPA STAR Grant #R830883.  ... 
doi:10.1890/0012-9658(2006)87[1472:abatrb];2 pmid:16869423 fatcat:qlbfav23m5bcde62lsxxvqverm

Tree Height Increment Models for National Forest Inventory Data in the Pacific Northwest, USA

Woo, Eskelson, Monleon
2019 Forests  
In addition to the current approach, five models were implemented: nonlinear exponential, log-transformed linear, gamma, quasi-Poisson, and zero-inflated Poisson models using both tree-level (e.g., height  ...  To account for negative height increment observations in the modeling process, a constant was added to shift all response values to greater than zero (log-transformed linear and gamma models), the negative  ...  Acknowledgments: We thank the many individuals involved in the design, field data collection, quality assurance, and processing of the U.S. Forest Service Forest Inventory and Analysis Program.  ... 
doi:10.3390/f11010002 fatcat:pky5g332tbhgldnfcc7ys5niri

Testing environmental and genetic effects in the presence of spatial autocorrelation

François Rousset, Jean-Baptiste Ferdy
2014 Ecography  
Marin for further discussion and help in tracking some references. Most computations were performed on the ISEM computing cluster platform. We thank R. Dernat for assistance in using this cluster.  ...  Acknowledgements -This work was supported by an exploratory program (PEPS) 'Comprendre les maladies émergentes et les épidémies'. We thank N. Yoccoz for helpful comments on the manuscript, Y. Lee, L.  ...  2009 , Storfer et al. 2010 , and similar questions arise in species distribution modelling (Algar et al. 2013) .  ... 
doi:10.1111/ecog.00566 fatcat:tr57gdvkjvfwdo3u6y4lmoaeue

Dealing with Varying Detection Probability, Unequal Sample Sizes and Clumped Distributions in Count Data

D. Johan Kotze, Robert B. O'Hara, Susanna Lehvävirta, Giuseppe Biondi-Zoccai
2012 PLoS ONE  
Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly.  ...  If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under-or overestimated the true  ...  Models assuming a quasi-Poisson distribution gave a very similar bias to the negative binomial models (data not shown), but this is not always the case.  ... 
doi:10.1371/journal.pone.0040923 pmid:22911719 pmcid:PMC3401226 fatcat:hfd25xoexrgp5d6dsbwakqvk3u

Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers

F. William Townes, Rafael A. Irizarry
2020 Genome Biology  
For scRNA-seq data lacking UMIs, we propose quasi-UMIs: quantile normalization of read counts to a compound Poisson distribution empirically derived from UMI datasets.  ...  Unique molecular identifiers (UMIs) remove duplicates in read counts resulting from polymerase chain reaction, a major source of noise.  ...  Specifically, we fit Poisson-lognormal models to seven public datasets from different tissues, species, and UMI protocols.  ... 
doi:10.1186/s13059-020-02078-0 pmid:32620142 fatcat:iilh5xi7pbgvjdxujdmgl6fjoq

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Carsten F. Dormann, Jana M. McPherson, Miguel B. Araújo, Roger Bivand, Janine Bolliger, Gudrun Carl, Richard G. Davies, Alexandre Hirzel, Walter Jetz, W. Daniel Kissling, Ingolf Kühn, Ralf Ohlemüller (+5 others)
2007 Ecography  
Here, we describe six different statistical approaches to infer correlates of species' distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed  ...  While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take  ...  In addition to these factors, spatial autocorrelation can also be caused by observer bias and differences in sampling schemes and sampling effort.  ... 
doi:10.1111/j.2007.0906-7590.05171.x fatcat:cfyswwzxgrcjlcb2tciaeehz3u

Estimating the effects of detection heterogeneity and overdispersion on trends estimated from avian point counts

Matthew A. Etterson, Gerald J. Niemi, Nicholas P. Danz
2009 Ecological Applications  
Point counts are a common method for sampling avian distribution and abundance.  ...  We also tested the effects of overdispersion by modeling both counts and removal mixtures under three statistical distributions: Poisson, zero-inflated Poisson, and negative binomial.  ...  Hawrot for their efforts in gathering the data presented.  ... 
doi:10.1890/08-1317.1 pmid:20014578 fatcat:eufx57uxhbccvncrmcfqpky6qi

Comparing Generalized Linear Models and random forest to model vascular plant species richness using LiDAR data in a natural forest in central Chile

J. Lopatin, K. Dolos, H.J. Hernández, M. Galleguillos, F.E. Fassnacht
2016 Remote Sensing of Environment  
In this context, we compared the suitability of random forest (RF) and a Generalized Linear Model (GLM) with a negative binomial error distribution.  ...  In these areas, overlapping distributions of thermopile sclerophyllos species, water demanding Valdivian evergreen species and species growing in Nothofagus obliqua forests occur.  ...  We ran GLMs with log link functions and Poisson, Quasi-Poisson as well as negative binomial distributed residuals for each response variable.  ... 
doi:10.1016/j.rse.2015.11.029 fatcat:unw2mrxebrejbod6dddwpwbgma

An Overview of Modern Applications of Negative Binomial Modelling in Ecology and Biodiversity

Jakub Stoklosa, Rachel V. Blakey, Francis K. C. Hui
2022 Diversity  
is playing a critical role, from generalisations based on exploiting its Poisson-gamma mixture formulation in species distribution models and occurrence data analysis, to estimating animal abundance in  ...  Indeed, overdispersion is often indicative of some form of biological aggregation process (e.g., when species or communities cluster in groups).  ...  We focus on the latter in this article, given its quadratic form. The former form allows for overdispersion only in a linear manner (similar to so-called quasi-Poisson models) [19] .  ... 
doi:10.3390/d14050320 fatcat:wzn7yiw7evhlfhghj7n2tnxiie

Testing Exogeneity of Multinomial Regressors in Count Data Models: Does Two-stage Residual Inclusion Work?

Andrea Geraci, Daniele Fabbri, Chiara Monfardini
2016 Journal of Econometric Methods  
AbstractWe study a simple exogeneity test in count data models with possibly endogenous multinomial treatment.  ...  We find differences in the finite sample performance of various likelihood-based tests, analyze their robustness to misspecification arising from neglected over-dispersion or from incorrect specification  ...  The tests are here obtained estimating a Poisson regression model while both DGPs involve a NB2 process.  ... 
doi:10.1515/jem-2014-0019 fatcat:zywlrva5nzcqtapfvmmgfq7o5u

Evidence of Absence Regression: A Binomial N-Mixture Model for Estimating Bird and Bat Fatalities at Wind Power Facilities [article]

Trent McDonald, Kimberly Bay, Jared Studyvin, Jesse Leckband, Amber Schorg, Jennifer McIvor
2020 bioRxiv   pre-print
With few observed fatalities, common statistical methods like logistic, Poisson, or negative binomial regression are biased and prone to fail due to complete or quasi-complete separation.  ...  In this paper, we describe the model, show its low bias and high precision via computer simulation, and apply it to bat fatalities observed on 21 wind power facilities in Iowa.  ...  We also wish to thank the dozens of Western EcoSystems Technology and MidAmerican field personnel who diligently collected the field data used in the examples.  ... 
doi:10.1101/2020.01.21.914754 fatcat:rfevjmpzd5h3nowifko7focisy

Analysis of a Three-Dimensional Point Pattern with Replication

A. J. Baddeley, R. A. Moyeed, C. V. Howard, A. Boyde
1993 Journal of the Royal Statistical Society, Series C: Applied Statistics  
Techniques for analysing three-dimensional spatial point patterns are demonstrated on data from a confocal microscope recording the locations of cells in three dimensions.  ...  A novel feature of the data is replication and nesting in a sampling design: multiple spatial patterns were observed from each of several animals. For this we develop a ratio regression approach.  ...  The next step in the analysis of the present data could be to model the process by an inhibitive or regular model such as a Markov point process in the standard way (e.g.  ... 
doi:10.2307/2986181 fatcat:hsxz4wkqzffvvasunkzmtxeyb4


J. Andrew Royle, James D. Nichols
2003 Ecology  
Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous detection probability model to estimate the underlying distribution  ...  Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability.  ...  In general, such information could be modeled in the Poisson mean, as in traditional generalized linear models.  ... 
doi:10.1890/0012-9658(2003)084[0777:eafrpa];2 fatcat:xsqhynisafby7b2sdiypzcj4ii

Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data

Pedro G. Nicolau, Sigrunn H. Sørbye, Nigel G. Yoccoz
2020 Ecology and Evolution  
In this case, the bias also increased assuming a Poisson distribution in the observational model.  ...  We found that density-dependence estimation was improved when explicitly modeling sampling error in scenarios with low process variances, in which differences in coverage reached up to 8% in estimating  ...  In this case, the bias also increased assuming a Poisson distribution in the observational model.  ... 
doi:10.1002/ece3.6642 pmid:33304489 pmcid:PMC7713978 fatcat:bfmu35gh3jcxfotsmm2fguw5m4
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