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Do not log-transform count data
2010
Nature Precedings
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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
A BAYESIAN APPROACH TO RETRANSFORMATION BIAS IN TRANSFORMED REGRESSION
2006
Ecology
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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]2.0.co;2
pmid:16869423
fatcat:qlbfav23m5bcde62lsxxvqverm
Tree Height Increment Models for National Forest Inventory Data in the Pacific Northwest, USA
2019
Forests
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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
2014
Ecography
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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
2012
PLoS ONE
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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
2020
Genome Biology
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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
2007
Ecography
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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
2009
Ecological Applications
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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
2016
Remote Sensing of Environment
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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
2022
Diversity
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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?
2016
Journal of Econometric Methods
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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]
2020
bioRxiv
pre-print
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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
1993
Journal of the Royal Statistical Society, Series C: Applied Statistics
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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
ESTIMATING ABUNDANCE FROM REPEATED PRESENCE–ABSENCE DATA OR POINT COUNTS
2003
Ecology
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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]2.0.co;2
fatcat:xsqhynisafby7b2sdiypzcj4ii
Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data
2020
Ecology and Evolution
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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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