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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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multiple linear regression for bounded variable

I am aware that there are special models that deal with bounded variables (binomial, logistic, beta regression) and all have different benefits and are used for different data types. However, I read ...
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Literature on conceptual understanding of beta regression

I am researching beta regression models to decide if they are appropriate for my data. My very first search yielded this basic introduction, that also describes the zero-one inflated beta regression. ...
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Evaluating model fit for glmmTMB with beta distribution

I am looking for a way to evaluate model fit (e.g. R2, %deviance explained) for the following model: m1<-glmmTMB(AUC_indep~woody+dispersal+log_densitys+log_seedwts+I(log_seedwts^2)+(1|modeltype), ...
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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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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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483 views

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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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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1answer
116 views

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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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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1answer
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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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1answer
458 views

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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1answer
101 views

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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2answers
315 views

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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1k views

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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1answer
141 views

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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2answers
587 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
40 views

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 ...