Questions tagged [beta-regression]
Beta regression is useful when the dependent variable is bounded, or when it has a ceiling or floor effect. It can also be used for modeling both the mean and the variance.
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Can Phi coefficient for intercept be negative?
I am working on beta regression model with two grouping variables (farm and years). Climatic variables are my predictors. Response variable is male proportion. I standardized all variables prior to ...
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GLM or beta regression, with proportion data, and many 0 and 1
I am trying to see if some anthropic variables (e.g., PopdensityAvg) explain animals' distribution. My dependent variable is the area occupied (...
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Calculating Mediation Indirect Effects using GSEM in Stata or R for Count (Discrete) Mediators
Estimating the following model in Stata helped me get the direct effects. This is a set of three models, a beta regression with the final outcome as the dependent variable, and two mediating negative ...
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Does survey R package allow me to do beta regression?
I have a complex survey dataset with a response (dependent variable) bounded between 0 and 1, where I have applied multiple imputation to the dataset to account for missing data. The response formally ...
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Beta regression for interaction terms without full rank? (R)
I have a series of beta regressions I have performed on the effects of tissue type, year, and age class on the eccentricity of ellipses, which varies between 0 and 1. I have created interaction models ...
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binomial GLM for proportion Vs Beta regression
Suppose that I have a dependent variable which is the proportion of persons infected with a certain disease out of the total number tested in different locations. Assuming the difference in ...
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Simulate a distribution from a fitted beta-regression model for a density plot in R [duplicate]
I have produced the following figure by simulating some values from a fitted gamma regression with a low AIC value that provides the closest approximation of my raw data out of all of my models, and ...
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Improving fit of underdispered beta regression model in glmmtmb
I have survey data where the outcome is the proportion of a research budget interviewees wished to assign to one of three different "types" of research into solutions for various issues. I ...
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Beta regression with success and failure raw data
I am analyzing data from cancer patients that underwent surgery for cancer removal. During surgery, the surgeon checked a variable number of lymph nodes to see how many had cancer in them. This is ...
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Modeling a 0-1 Bounded Dependent Variable That is Not a Proportion/Probability
I have seen many applications of beta regression when dependent variables are bounded between 0 and 1 (proportions, probabilities, etc.).
However, would beta regression be appropriate when my ...
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Interpretation of betareg coefficients where observations transformed to account for y=0 or y=1
I am running a beta-regression using betareg in R (with default logit link function). My response variable is a proportion, and may include 0 and/or 1. I've transformed the data following the betareg ...
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Why does MCMC estimate the variance in a logit-normal model incorrectly?
I am trying to estimate the variance $\varepsilon^2_X$ in a simple logit-normal model of the form
$ \sigma^{-1}(U) \sim \mathcal{N}(\mu_U, \varepsilon^2_U)$
$ \sigma^{-1}(X) \sim \mathcal{N}(\sigma^{-...
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How to implement a mixed model using betareg function in R?
I have a dataset comprised of proportions that measure "activity level" of individual tadpoles, therefore making the values bound between 0 and 1. This data was collected by counting the number of ...
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Beta regression coefficient interpretation
I'm trying to use beta regression on a data set where the response variable is in percentage (i.e. between 0 and 1), so let's say it's the unemployment rate. I'm having trouble wrapping my head around ...
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Can you run a mediation analysis using beta regression
When running a beta regression in R I am interested in seeing if there are any potential mediators to my primary outcome. My primary outcome is bounded between 0 and 1 and I therefore am unsure I can ...
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Beta regression fitted values
I have a beta regression model in R, have generated predicted (fitted) values based on my data, and plotted lines of those fitted values on a scatter plot of the actual data. I'm most used to GLMMs, ...
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Converting dispersion to standard deviation in a beta regression
I'm unsure about the relationship between dispersion estimates (precision^-1) from beta regression models (log link) and the standard deviation.
The left panel is from a glmmTMB model ...
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What is the difference between beta regression and quasi glm with variance = $\mu(1-\mu)$?
First let me give some background; I will summarize my questions at the end.
The Beta distribution, parameterized by its mean $\mu$ and $\phi$, has $\operatorname{Var}(Y) = \operatorname{V}(\mu)/(\...
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Beta regression - simultaneously tracking all components so that proportions sum to 1.0
I am trying to fit a beta regression model in R with the outcome variable representing proportions, so that the model accounts for all of the constituents of the whole fraction. I am unclear how to ...
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How to relate prevalence to factors with multivariate analyses model (GAM beta inflated)?
While analizing the prevalence of cows to brucellosis (illness), and in order to relate it to a set of factors like country, state, and detection technique, I need to apply a multivariate analysis ...
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Dominance analysis with a random-effects beta regression: nested random effects throw error
The goal
I want to run dominance analysis on a mixed-effects beta model, to approximate the relative importance of a set of predictors (2 factors, 1 scaled continuous, 1 continuous with splines). The ...
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Beta regression: slope of scaled predictor
I want to fit a beta regression with an scaled continuous predictor, and express the slope in terms of proportion (not at the transformed, log-odds scale). In other words, I would like to express the ...
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Bounded variable: beta regression or switch to ratio?
My task is to study factors that influence the composition of labor force. The latter consists of two types of workers, full-time and part-time. My first approach was to run an OLS regression for the ...
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In Beta Regression we obtain predictions of the mean response, do we therefore assume that the response is B(mu, var) around those predictions?
The title question here is a bit awkward because I'm really asking if this illustration I've drawn is true:
Suppose we have a Beta Regression of one predictor, X, which is used to model both the ...
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Regression Bounded Between -1 and 1
I am performing a meta-analysis on the response of rodent abundance to clear-cut logging. I have data from multiple sites, across multiple years, and for different species of rodents, and am using ...
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Comparing models with the betareg packpage
I'm having problems using betareg. I have a dataset that always shows different results depending on how I perform the analysis. I'm using ...
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Estimating Exponential Decay Rate and its confidence interval from Beta Regression Odds Ratio fit
I am working with a random variable that is bounded between 0 and 1, and its mean decreases exponentially over time. I am seeking to estimate this exponential decay rate with its corresponding ...
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How to model proportion data from an online experiment?
I have designed and run an online experiment in which we've slightly changed parts of a web page. Let's say users visit our website to place food orders and the order funnel looks like this: home --&...
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Overdispersion in a beta regression? (DHARMa package)
I'm trying to run a beta regression to predict my dependent variable Consistency, which has values between 0 and 1.
Here is the distribution of Consistency values in my dataset:
I originally tried ...
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emmeans for betareg is giving me identical arrow ranges when plotting comparisions = T
My response is a ratio (length of a discoloration disease in the plant divided by the height of the plant), so is always (0, 1). Actually, sometimes it could be [0, 1), i.e., including zeros.
As I ...
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Interpreting coefficients of beta regression
I have implemented a beta regression and am a little confused on how I should interpret the coefficients of my model. For context, both my independent variables and dependent variable are expressed in ...
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Interpreting coefficients of beta regression
I have implemented a beta regression and am a little confused on how I should interpret the coefficients of my model. For context, both my independent variables and dependent variable are expressed in ...
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Explanatory model for zero-one inflated bimodal data with random effect and binary indepentent variable
I'm trying to evaluate the influence of a single binary explanatory variable on a 0-1 scale response, with one grouping factor. The response variable is generally 0-1 inflated. The simplest solution ...
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how to interpret estimates from Beta GLMM with dummy explanatory variables
I have results of an experiment where each person had to estimate a share of certain types of city dwellers in two cities (A and V), and participants were assigned into one of two treatments (FIN or ...
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How to write a generalized additive model, fitted in R programming language, in a mathematical form? [duplicate]
I have fitted a model in R programming language. My dependent variable is disease severity and my predictors are weather variables. How can I write this model in mathematical form for a manuscript? Is ...
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How to account for different trial durations in mixed models?
My experiment was conducted in multiple years. Each year, plants were sown in an infested field and then harvested after a certain time. There was a weather station to record weather data. I would ...
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Truncated Poisson vs ordered multionomial + beta regression
I want to model a random variable that takes values between 0 and 1, and where 0 and 1 are included. Zero and one are possible values of the random variable and occur frequently. I have several ...
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Model specification for skewed proportion as dependent variable
I am struggling with assessing the best weighted regression type/model specification for my problem.
The goal is to determine influence of independent variables towards the outcome (dependent variable)...
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Why beta regression?
According to http://r-statistics.co/Beta-Regression-With-R.html, the topline remark is:
Beta regression is used when you want to model Y that are probabilities themselves
Grammar aside, one may ...
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Getting a warning in beta regression model "Warning: no valid starting value for precision parameter found, using 1 instead"
I'm getting a warning message (Warning: no valid starting value for precision parameter found, using 1 instead) while fitting a beta regression model using ...
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How to account for multicollinearity between weather variables in generalized additive models?
I investigated the effect of weather variables on disease severity. My response variable is proportion of disease severity observed in different years. The study is conducted over 10 year and disease ...
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Is there a way to convert beta regression coefficient in odds ratios?
I'm currently working on a meta analysis and half of the included papers only reported the beta coefficient. I wanna pool the odds ratios and am now wondering if there is a way to convert beta ...
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Can the Beta-regression be written in the GLM form?
The Beta distribution is:
$$p(y)=\frac{\Gamma(\alpha+\beta)}{\Gamma(\alpha)\Gamma(\beta)}y^{\alpha-1}(1-y)^{\beta-1}
$$
It's part of the exponential family.
We can reparametrize this with using mean ...
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How do I interpret a betareg coefficient of 6.6970 for a categorical variable with only two categories, given that the response is a proportion?
I cannot seem to find an exact answer to my question online. I used the betareg package in R to run a glm with a response variable that is a proportion, so it is between 0 and 1. One of my predictor ...
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How to improve model's predictive accuracy brms / rstan
General question: How can you improve a model after seeing that it poorly predicts your data (i.e. posterior predictive distribution doesn't recover your data well)?
I am fitting a multilevel beta ...
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Beta regression (proportions) with phylogenetic comparative analysis?
Is there a package in R that allows phylogenetic comparative analysis of proportion data (i.e. a beta distribution)?
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Best regression model for ratios of a zero-inflated Poisson with a zero-truncated Poisson random variables?
I am working with data in which my dependent variables underlying probability distribution is a ratio of correlated ZTP-ish (ZTP = Zero-Truncated Poisson) random variables $Y = \frac{M}{C}$ with $C \...
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Modeling the precision and location parameters in beta regression
Is there any technical or substantive reason to typically want to ensure the location $\mu$ and precision $\phi$ parameters in the beta regression model include the same fixed or varying predictors?
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Why does my Cullen and Frey Plot indicate a Beta distribution even though it is not a probability distribution?
I am trying to build a model that will estimate people's willingness to pay for a certain good.
My dataset is comprised of more than 1000 observations and 30 variables. This is how my distribution ...
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GLMMadaptive - Hessian matrix problem Hurdle Beta Model
Data:
I have a percentage (or proportion see paragraph below) outcome dataset with a high number of zero's. I have therefore attempted to run a hurdle beta model using the GLMMadaptive package in R. I ...