Questions tagged [offset]
A variable with a fixed coefficient of 1. Offsets are commonly used in Poisson regression to allow the modeling of rates instead of counts.
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Parameter estimate interpretations in lm with offset
I want to analyze flight times of an insect (in function of several weather parameters), but these are done at different distances.
One option could be to calculate the speed and analyze this, or what ...
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Is it reasonable to apply different offsets to different species in community analysis?
I am using the manyglm function from the mvabund package. I have a site X species/family dataset of counts. One organism in the community is vastly more abundant than the others (by multiple orders of ...
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Is it possible to have rate predictions which are greater than 1 with Poisson regression in r?
I was trying to fit the Poisson rate regression and predict the rate by using StanMoMo in R. However, when I tried to extract mufor(The predictions were saved in this variable) from the result. Few ...
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(Ab)Use of offset() in Poisson GLM to weight the damaging effect of counted insect stages
According to A.F. Zuur et al. (2009) in 'Mixed Effects Models and Extensions in Ecology with R', p. 239ff and this post: When to use an offset in a Poisson regression?, ...
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Offset using Poisson distribution
I get everything but the two sentences are confusing me.
Offset is a variable that serves to consider the different exposures of different observation. When properly included, the target variable is ...
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How to impose restrictions on a regression using offsets?
An offset is a variable that is included in the regression but without coefficient (i.e. the coefficient is fixed at/assumed to be 1). I want to impose restrictions on my regression and I read that it ...
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Does a GLM where the dependent variable is a rate without offset produce the same result when a count with offset is used?
I have the following two models in Python:
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How to account for proportionality of predictors in a poisson regression
I am looking to conduct an analysis to test which variables (diagnosis, ethnicity, level of care) significantly predict the number of self-harm incidents a patient has over 2 years (observational data)...
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How to correctly include an offset in a bernouli model in JAGS/WINBUGS (Only one success, but number of choices can change)
I am trying to fit a Bernoulli model in Jags. This is for mate choice - whether a male interacts with a given female out of a selection of females. For the purpose of the model they only get one ...
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Offset variable in a Poisson regression measured with error
It is known that measurement error in predictors lead to a bias toward zero, and also bias other predictors’ estimates:
The effect of covariate measurement error on coefficients in regression with ...
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How to interpret model estimates of a Glmer (poisson) with count data, offset term to get a rate, and random effect
I am trying to apply a glmer on syllable-count data obtained from bird song. I include the record ID as a random factor (1 | rec_ID) due to variation in the number of songs per recording, and consider ...
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Poisson GLM Offset Exposure Question (from a noob)
Hi i am actually not an actuary but i'm currently working on an ML project on insurance pricing. The pricing is calculated by multiplying Claim Frequency and Severity, correct?
I'm currently using ...
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how to add offset for Poisson-GPR using GPML package? [closed]
I'm using the popular GPML package in MATLAB for both Poisson and NB regression. Is there any way to add offset as easily as glmfit()?
Specifically, assume there are N obesrvations, I want $\log(\mu)=\...
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How should I introduce an OFFSET term for a BINOMIAL response variable?
I have a binomial response variable -proportion of removed fruits, or plant visited or not visited by a frugivore- in a GLMM. I would like to control for differences in the sampling effort (time) ...
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How to interpret coefficents when you have an offset?
I'm measuring counts of birds as a function of the time (in months) across three parks (NP), as well as the presence of carcasses and season. I'm trying to find out whether the population is ...
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How can we incorporate an offset into a software library which performs least squares without offset
Disclaimer: this is not homework, just preparation for an exam I'll be taking
How do I incorporate an offset term into a software library that performs least squares (without offset)?
Let me give a ...
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Count vs. continuous predictors in Poisson regression with offset
I'm having a conceptual problem related to using different types of predictor variables (i.e., count data vs. continuous data) in Poisson regression.
My field method was walking transects and counting ...
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negative binomial glm: issues with model diagnostics when using offset term
I'm trying to model count data using a negative binomial glm with an offset in R and am having some issues with getting the model to fit properly when I use an offset term. Here is a reproducible ...
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In Poisson models with an offset, should performance metrics (such as deviance) be calculated in terms of raw counts or counts per exposure?
For context, I need some metrics that can compare a standard Poisson regression (with population offset) to a random forest regressor with Poisson criterion.
The test predictions for both methods are ...
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Is "vanilla" random forest regression appropriate when dependent variable is a rate (i.e. per 100 people)?
To add a little more context, I am working with a dataset from which I want to predict the population-normalized count of emergency department visits on county level, with 50+ independent variables. ...
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Offset or weight in binomial GLM - account for distance to road on animal sightings
I am building a species distribution model for an animal, using data collected by community members when they sight this animal. My first step is to fit a generalised linear model with family binomial ...
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Accounting for sampling effort of independent variables in a regression analysis
I would like the test whether the frequency of a cellular structure on a histology section is associated with (binary) patient outcomes. This would be a simple logistic regression of i.e. ...
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Offset in Poisson GLM with log link function where I have values equal to zero
I am trying to build a GLM model (poisson family) using python statsmodels package on train data. The data I have contains categorical values as exogenous variables and numerical values for my target (...
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Does a constant offset term meaningfully influence Poisson GLM?
If my offset term is a constant value, does this change the outcome of a Poisson GLM regression?
I have survey count data that we summarize as a rate (Counts/Area-Surveyed). In this case, transect ...
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Incorporate Weights/Offsets with Nonparametric Models
I am modeling pure premium in R. I have read that pure premiums are usually modeled using a Tweedie distribution (glm). There is generally an offset or weight added to the model, such as an exposure. ...
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Can offset variables be used in binomial logistic regression models?
When I look up what exactly the offset is doing, I only see references to poisson or negative binomial models. Neither of those analyses work for me because I do not want to predict counts. I want to ...
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Inclusion of values that can only be zero in Poisson glmer
I have carried out a biological experiment in which the dependent variable is female propensity to mating, measured as the number of times a female animal accepts a mating attempt from a male.
I have ...
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Pair-matched count regression in R with offset?
I need to conduct a pair-matched count regression in R.
Specifically, my data looks as follows:
ID
Exposure
Occurrence
Area
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0
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1
5
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0
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I need the ...
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When to use offset in binomial glm
I am trying to model the number of successes in data where the number of trials is not fixed. I am trying to fit a binomial generalised mixed effects model, with the number of trials as an 'offset' ...
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How to include population size in difference-in-differences analysis
I'm trying to estimate the effect of a certain policy intervention on the count of violent incidents in communities which received that intervention, compared to communities which didn't. I'm trying ...
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Poisson regression with offset - help with fit and visualization
My goal is to understand the relationship between the number of worms found in a plot of land and the percent silt that makes up the soil. The plots of land have been investigated to different extents ...
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using per capita or raw counts for epidemiological regression analysis
I have two datasets. To simplify, they look something like this:
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Does offset always have to be on log scale with NB GLMM?
I'm using a negative binomial GLMM with R package lme4 to detect differences in time mothers spend feeding before and after birth (inf_cat).
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Choosing the best family and link function for a GLM
I'm new to GLMs and I need to do several GLM using a kilometric abundance index (non integer, but calculated from a count) as the dependent variable and several habitat traits as the independent ones.
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Do offsets consume degrees of freedom?
In a model with some offset variables (variables with pre-determined regression coefficients), do these variables consume degrees of freedom, with regard of e.g. information criteria?
Pro: You can ...
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GLMM: How to impose a specific parameter (intercept or slope) for the model?
Good afternoon,
I would like to know if it’s possible and how to specify parameters in a GLMM.
Let’s take the example of a GLMM with random intercepts. In the following equation, the vector of fixed ...
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Modelling catch rates: difference between Gamma and poisson distribution
I am confused about the difference between modelling counts (i.e. catch) using a poisson distribution with an offset (i.e. effort) and modelling catch per unit effort using a gamma(link=log) ...
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Can I partial out covariates with true coefficients known in Logit?
Suppose the model is
$$ \ln(\frac{P_{ij}}{1-P_{ij}}) = X_{ij}\beta_0 + A_i + A_j + \epsilon_{ij}, $$
The unit of observation is at $ij$ level, and $A_i$ and $A_j$ are coefficients on the dummy for ...
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Understanding offsets for continuous variables
I'm currently trying to write a linear model with data from some behavioural experiments with termites.
I started to read Ben Bolker's "Ecological Models and Data in R", which has been a ...
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Modelling overdispersed rate data using a negative-binomial distribution
A quick overview of the analysis I'm wanting to do:
I am wanting to analyze the relationship between habitat factors and the capture of my research species over a network of traps, in order to be able ...
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Can weights be used in place of offset in Tweedie model
I have seen evidence that Poisson regression can be run with either offsets or weights for time and both give the same results. However, I have noticed that the same is not true for Tweedie. I have ...
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mvabund package can't handle offsets?
I have a set of fish data from a lake. I am trying to see whether the local fish community differs depending on the location within the lake (North, East, West), the presence of an island at the ...
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How to handle a constant parameter in a Poisson regression?
I have a Poisson regression model with rate, $\lambda$, defined as $ln (\lambda) = \alpha + \beta + \gamma$. Here $\alpha$ and $\beta$ change and $\gamma$ is 0.5 for each observation. $\gamma$ is ...
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Variance of negative binomial given an offset
Given observations $Y_1, \ldots, Y_n$ from the negative binomial distribution, $NB(\mu, \theta)$, and assume that we model the mean with a GAM:
$$\log E(Y_i) = \log \mu_i = \log t_i + f(x_i),$$
where $...
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Interpretation of quasi poisson regression with offset
I am trying to find out how to correctly interpret the coefficients for a Poisson regression. My main outcome of interest is the number of antibiotics prescribed (count) or the rate of antibiotics ...
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Incorporate offset into mgcv GAM smoothing
When developing mortality models, I often have the following problem: I have a prior/base rate table and mortality experience data from a population of interest, and I need to develop factors on top ...
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How to adjust for exposure time in a binomial model
I have several binomial (logit) models that predict the probability of various binary outcomes (e.g., incurring any costs for health care treatment, having a chronic disease). My case and control ...
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Best GLM to model a random variable that represents a count over a non-fixed interval of time
The random variable on which I am seeking to fit a GLM is the number of times a patient has a blood glucose level measurement above a specified threshold before they are escalated onto a stronger ...
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