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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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R: How to calculate power to detect a change in mean beta reg.?

I'm interested in calculating the power to detect a change in my mean response variable by a certain effect size, but I'm not sure how to start. My Y variable is mean plant cover 0-100% cover (mean of ...
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Difference between regression methods

When to use logistic regression and when to use beta regression in statistical modeling for given data? How do know the difference between them? And when can I fit just a linear regression and not ...
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Beta regression-dealing with small number of 0,1 values

I have a small dataset for 100 participants. The dataset includes repeated 'tests' over a course of a week. A test can have the binary outcome of pass or fail, and the same number of tests are not ...
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How to resolve the residual versus predicted quantile devation (Dharma plot)?

I have been trying to perform beta regression modeling with random effects. I have sex ratio (0.561, 0.765 etc) as the response variable, and climatic variables + years (1970-2021) as predictor ...
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4 votes
2 answers
242 views

What causes the parameter phi (precision) to be very small in beta regression (by betareg in R)?

I tried to do a beta regression for a variable affected by age and intimacy, but it did not work well. The value of phi (precision) estimated by maximum likelihood method is very small, and when I ...
TomoChang's user avatar
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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 ...
Rahul's user avatar
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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 ...
ElizaBeso000's user avatar
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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 ...
Wagathu's user avatar
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1 answer
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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 ...
ElizaBeso000's user avatar
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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 ...
Tomas Bencomo's user avatar
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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 ...
Brian Lookabaugh's user avatar
2 votes
1 answer
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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 ...
branwen85's user avatar
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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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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 ...
theworldistoosmall's user avatar
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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 ...
Jack's user avatar
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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 ...
nullglob's user avatar
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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 ...
Adonis Cedeño's user avatar
3 votes
1 answer
142 views

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 ...
M. Riera's user avatar
1 vote
1 answer
182 views

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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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 ...
Mikhail's user avatar
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1 answer
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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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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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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 ...
Diego Pujoni's user avatar
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199 views

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 ...
AndresvS's user avatar
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1 answer
209 views

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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1 answer
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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 ...
falc's user avatar
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2 votes
0 answers
52 views

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 ...
falc's user avatar
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3 votes
0 answers
85 views

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 ...
dr Inken Ergy's user avatar
1 vote
1 answer
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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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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 ...
Philipp Chapkovski's user avatar
1 vote
0 answers
34 views

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 ...
Ahsk's user avatar
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1 answer
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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 ...
Ahsk's user avatar
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2 votes
1 answer
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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 ...
user2521204's user avatar
2 votes
2 answers
65 views

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 ...
FredrikAa's user avatar
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1 answer
239 views

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)...
Meowcapone's user avatar
6 votes
0 answers
225 views

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 ...
AdamO's user avatar
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1 vote
1 answer
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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 ...
Ahsk's user avatar
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1 vote
0 answers
78 views

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 ...
Ahsk's user avatar
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1 vote
1 answer
8k views

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 ...
Léonie's user avatar
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4 votes
1 answer
667 views

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 ...
Maverick Meerkat's user avatar
4 votes
2 answers
1k views

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 (...
LT17's user avatar
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1 vote
1 answer
246 views

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 ...
Jefferson Bruno Bretas's user avatar
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0 answers
52 views

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 \...
DeadKarlMarx's user avatar
1 vote
1 answer
262 views

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 ...
Will's user avatar
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6 votes
1 answer
286 views

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?
socialscientist's user avatar
1 vote
2 answers
246 views

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)?
Picapica's user avatar
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4 votes
1 answer
1k views

Logit GLM and logit beta regression: Practical difference in the interpretation of the coefficients?

Terminology: By logit GLM I mean a generalized linear model with a binomial distribution and a logit link function. By beta regression I mean beta regression with a logit link function. I understand – ...
dwolfeu's user avatar
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6 votes
3 answers
1k views

Proportion data with number of trials known (and separation?): GLM or beta regression?

I perform a lot of bioassays in which I score mortality not on individuals, but on groups of individuals as a proportion (the denominator, i.e., number of trials, is known): Sample Data: ...
RegalPlatypus's user avatar
4 votes
1 answer
323 views

Beta regression shows a weird plot

I am trying to model the relationship between my response 'crop coverage [%]' ~ weed coverage [%] + Soil Moisture [%] using R. Since I am dealing with proportions, I chose to do a beta regression. ...
Effigy's user avatar
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