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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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Is fair to compare Dirichlet to a Multivariate Beta regression?

I am conducting some analysis on my data I found a strange behavior and would greatly appreciate some guidance or suggestions. I am trying to investigate the effect of a categorical variable (cl) to ...
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Relationship between Beta regression of Y on X and linear regression of X on Y. (where Y is a proportion)

I am trying to model the relationship between school district funding and a district's poverty rate. If I treat funding as the independent variable then the dependent is a proportion on [0,1]. This ...
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Modelling and interpreting brms output

I do apologize in advance for this might be very basic questions. I am not really familiar with Bayesian statistics and too, unfortunately, this is the very first time I am analysing data in general. ...
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Beta Regression Model Selection with CV Lasso in R

Is there a package that will do a cross-validatation with regularization for beta regression in R? I'm looking for an equivalent of glmnet for the betareg package.
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Fitting Beta Distribution Parameters to Y conditional on X

I have a bi-variate data set where Y is in [0,1]. X is some measure of intensity and in this example is (0,~200) though there is no hard upper bound. X has a strong positive skew but I am not ...
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Modelling a percentge as a dependent variable

I have a dataset containing 4 variables: Y - the dependent variable. This is a percentage of students in a school that choose to take an external exam. The values vary from 20% to 70%. X - the ...
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Should I use a binomial glm, beta regression, uniform continuous distribution or nls with logistic regression for probabilities?

I made an individual based model in which there is a population of three types of individuals (lizards) that disperse randomly until they encounter another individual that has a beneficial effect on ...
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Beta regression - interpret coefficients using loglog link

Although a number of similar questions (some of them duplicates) have been asked around the interpretation of the coefficients from a beta regression, these seem to be focused on models that have used ...
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Beta regression - calculate predicted value from coefficients using loglog link

Firstly, I would like to say, I have read a great post but it doesn't quite answer my question. This post came very close, but I still couldn't solve my issue from it. I would like to be able to run ...
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Negative lower confidence limit in beta regression?

I fitted a beta regression on some proportion data using the betareg() function from the betareg package. The proportion was ...
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How to compare two random intercept beta regression model for one predictor on two different outcomes?

I have a clustered data set ,where two outcomes variables are rate/proportion type (Y1, Y2) and a binary predictor variable (X1). I am fitting random intercept beta regression for adjusting the ...
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Regression when both the predictor and outcome variables are proportions

I am using $X$ The estimated pre-game win probability of a sporting team playing on its Home field (estimated according to a certain model) to predict $Y$ Actual proportion of points scored by ...
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Beta regression estimates and confidence intervals on response scale

I'm using GLMMadmb for my beta regression. I'm having a bit of trouble. I understand beta regression uses the logit link function and I know how to get from logits to probability. Here's selected ...
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Beta regression where fractional response adds up to 100%?

I have a data set of people switching brands. Say #people switching from Brand A to Brand B, C or D. My data looks like this ...
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Weighted least squares estimator

I have this linear model: 𝑦𝑖 = 𝛽𝑥𝑖 + 𝜖𝑖, 𝑖 = 1, … , n with variance proportional to the covariate, like $𝐸(𝜖_𝑖) = 0 $ and $𝑉𝑎𝑟(𝜖𝑖) = 𝜎^2_{𝑥𝑖}$. I need the weighted least squares ...
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Reporting betareg outcome - how to compare non-nested models?

I am looking for advice how to gain and report results using beta regression for an ANCOVA-like model. My model is as follows: ...
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bayesian regression with a limited dependent variable

Good Morning, i have an answer regarding bayesian regression. I have studied the jags package with a book, but i dont get how to do a simple regression with a dependent variable that can take values ...
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Logit transformation or beta regression for proportion data

I'm interested in knowing about the difference in interpretation between (1) linear regression on a logit transformed variable with values between 0 and 1 and (2) beta regression where the values ...
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Attempting to interpret both Beta Regression and transformed DV model results

After reading a good amount of the answered questions on interpreting Beta Regression results (Best explanation here) and reading through the Betareg vignette, I still feel a lack of confidence ...
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Specifying nested random factor in emmeans from a gamlss object

I am trying to use the package emmeans with a gamlss object with a mixed model using a beta distribution. I am unsure as to the best way to use the emmeans function to include my nested random effects....
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Diagnostic residuals for Beta GLMM weighted by sample size (Meta-analysis) using glmmTMB

I am conducting a GLMM for a meta-analysis using the beta distribution with the package glmmTMB. My response variable is a vector of correlations (No exact 0 or 1), but Fisher’s transformation fails ...
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betareg returns values outside of bounds [closed]

The betareg function returns estimates for mu and phi. I received the following output for ...
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Beta regression (betareg) with caret and train [closed]

I have a dataset with a dependent in range (0,1) and numerical/categorical predictors. Chiefly to streamline the code and easily accomplish cross validation (feature selection/model fitting), I would ...
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Standardised coefficient interpretation (beta reg. with logit link)

If I standardize the coefficients (scale() command in R) of a beta regression with a logit link, how do I interpret them? I would say: Of how many standard ...
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Why use the logit link in beta regression?

Recently, I have been interested in implementing a beta regression model, for an outcome that is a proportion. Note that this outcome would not fit into a binomial context, because there is no ...
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Mixed model with proportions, zero- and one-inflated

My dataset has observations of bees visiting flowers to collect nectar. A visit can either be "pollination" or "nectar robbing" (the bee collects nectar from a hole through the side of the flower). ...
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Homoscedasticity and normal distribution on proportion data - beta regression necessary?

I have a couple of datasets with proportion data. For some datasets the values are nicely normal-distributed and show homoscedasticity. Is it fine to run a two-way ANOVA or Scheirer-Ray-Hare test? Or ...
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How do I specify a random effect in Bayesian beta regression model?

My response data are proportions that I want to model with one continuous predictor and a random effect of group. Here's my winbugs code: ...
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interpreting results of beta regression [duplicate]

Looking here at the beta reg packge: https://cran.r-project.org/web/packages/betareg/vignettes/betareg.pdf The code below is using a categorical batch variable and a continuous temp variable to ...
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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 conduct significance testing for percent outcome based on summary statistics only?

I have three groups A, B, and C, with corresponding sample size. I have gender variable as a binary variable, with M vs. F. For each group, it's summarized into "percentage woman". I only have the ...
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Classification when each level has probability assigned to it

The response variable in my dataset is a factor with six levels. For each observation, each level has been assigned a probability to be interpreted as the probability that the given observation is ...
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Zero inflated beta regression using gamlss for vegetation cover data

My goal is to analyse vegetation cover data. The way the data collection works is that you throw a quadrat (0.5m x 0.5m) in a sample plot and estimate the percent cover of the target species. Here is ...
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Regression model to predict an individual's race

I have a database of individuals containing data about age, gender, place of living (census tract level) and income but nothing about race. Beside this, I have aggregate race data at census tract ...
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Why Beta/Dirichlet Regression are not considered Generalized Linear Models?

The premise is this quote from vignette of R package betareg1. Further-more, the model shares some properties (such as linear predictor, link function, ...
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About Effect Coding: It is possible to include μ “mu” and all the τ “tau” in a β matrix? [closed]

Is it mandatory to have a comparison group (one "tau" is coded as -1 and it does not have its own column)? If it is mandatory, can you explain why? I am trying to represent the model Y=Xb+e in ...
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Which approach can be used to regress sleep time on brain mass, in this data set?

I was reading this blog post: https://htmlpreview.github.io/?https://raw.githubusercontent.com/avehtari/BDA_R_demos/master/demos_rstan/sleep.html the author describes a model to predict how many ...
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interpretation of betareg coef

I have a data that where the outcome is the proportion of a species observed in an area by a machine on 2 separate days. Since the outcome is a proportion and does not include 0 or 1 I used a beta ...
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Beta regression with categorical predictor variable

Is it ok to run a beta regression with proportion data (as the y variable) and categorical predictor variables? i.e., I know the R etc. will often do the conversion for you, but I just want to make ...
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Beta distributed variable standard deviation and mean

I'm new to beta regression and I'm trying to figure out what the appropriate descriptives are to report when you have a beta-distributed variable. If I have a two-level IV predicting a beta-...
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Why are my beta regression results biased?

I would like to use the betareg package, and started with some simulations to ensure I understand how it works. I seem to be getting biased coefficient estimates in my simulation. I have made my ...
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Logistic regression for a continuous dependent variable

I am trying to model a response variable, the weight of a variable (can't be thought of a binomial distribution as it involves no success/failures), that falls between 0 and 1. That is, the response ...
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Interpretation of cloglog model in layman's terms

I fitted a beta regression model via MCMC with a complementary log-log link function. Is there a way to interpret it in a layman's terms? The estimates of the model are: \begin{align} \beta_0 &=...
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Bias in beta regression

I just wanted to check how good my Beta reg model was at recovering true values of the parameters, and I found surprisingly large differences. Same results when using the "betareg" package. Here is ...
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576 views

Standard errors in beta regression

I am trying to estimate Beta regression model with Matlab based on Ferrari & Cribari-Neto (2004) paper (see https://www.jstatsoft.org/article/view/v034i02/v34i02.pdf). I have encountered a severe ...
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1answer
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Appropiate model for $Y \sim f_1(X) + f_2(X) + f_3(X) + … $, $Y \in [0,1]$

I wish to model the following relationship $$Y \sim af_1(X) + bf_2(X) + cf_3(X) + ..., Y \in [0,1]$$ where $Y$ is a response (a percentage divided by 100) and $X$ is a covariate which I want to model ...
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How do I find the equation of a predicted beta regression curve?

The formula (i.e. y~x) used for beta-regression is unclear to me. I would like to know what the resulting equation would be for a predicted beta-regression curve with the following summary output: <...
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standardized coefficient interpretation in logs from beta function [duplicate]

How can I interpret the beta regression from regressing lny on lnx, or lny on x etc. For example in Stata I make this regression using beta function: reg lny lnx z t, beta robust this gives me usual ...