Linked Questions

2
votes
2answers
2k views

Logistic Regression -- Use of real values between 0 and 1[as opposed to two classes as negative:0 and positive:1] [duplicate]

I just wanted to confirm if this was correct :) For logistic regressions, do the outputs in the training set are actually no different than the outputs that we get as predictions? Is the only reason ...
2
votes
1answer
2k views

Predicting values in a given range [0, 1] (not probability) [duplicate]

I need to predict the impact of a set of node failures in a network, based on 2 features: the fraction of failed nodes and a measure of their network centrality. Failure of less important nodes will ...
0
votes
0answers
977 views

Which regression model to use for a probability as dependent variable? [duplicate]

My dependent variable is a probability. As such, values lie between 0 and 1. The most common values are 0, 0.5, and 1 each occurring in 20% to 30% of the observations but any value in between is ...
0
votes
0answers
60 views

How to build a model with a continuous response variable bounded from 0 to 1? [duplicate]

How to build a regression model with a continuous response variable bounded from 0 to 1? I think it is not logistic regression, where I am not predicting a binary response variable, Right? Sorry ...
1
vote
0answers
34 views

Method to predict outcome as percentage of two categories? [duplicate]

In real world example I have elemental composition data for groundwater, which is known to be coming from two sources. I have control data where all predictors are from source A and data where all ...
0
votes
0answers
16 views

Training logistic regression model on class probabilities rather than class labels [duplicate]

I would like to train a binary logistic regression model, but instead of the dependent variable being a class label (ie: 1 or 0), I would like it to be a probability distribution over the possible ...
66
votes
5answers
23k views

How small a quantity should be added to x to avoid taking the log of zero?

I have analysed my data as they are. Now I want to look at my analyses after taking the log of all variables. Many variables contain many zeros. Therefore I add a small quantity to avoid taking the ...
33
votes
3answers
26k views

How to do logistic regression in R when outcome is fractional (a ratio of two counts)?

I'm reviewing a paper which has the following biological experiment. A device is used to expose cells to varying amounts of fluid shear stress. As greater shear stress is applied to the cells, more of ...
32
votes
3answers
3k views

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, ...
19
votes
3answers
10k views

What is the relationship between the Beta distribution and the logistic regression model?

My question is: What is the mathematical relationship between the Beta distribution and the coefficients of the logistic regression model? To illustrate: the logistic (sigmoid) function is given by $...
13
votes
3answers
19k views

What are the issues with using percentage outcome in linear regression?

I have a study where many outcomes are represented like percentages and I'm using multiple linear regressions to asses the effect of some categorical variables on these outcomes. I was wondering, ...
20
votes
1answer
13k views

How to fit a mixed model with response variable between 0 and 1?

I am trying to use lme4::glmer() to fit a binomial generalized mixed model (GLMM) with dependent variable that is not binary, but a continuous variable between zero ...
20
votes
2answers
6k views

Why exactly can't beta regression deal with 0s and 1s in the response variable?

Beta regression (i.e. GLM with beta distribution and usually the logit link function) is often recommended to deal with response aka dependent variable taking values between 0 and 1, such as fractions,...
10
votes
4answers
8k views

Extending logistic regression for outcomes in the range between 0 and 1

I have a regression problem where the outcomes are not strictly 0, 1 but rather in the range of all real numbers from 0 to 1 included $Y = [ 0, 0.12, 0.31, ..., 1 ]$. This problem has already been ...
6
votes
2answers
13k views

Percentage as dependent variable in multiple linear regression

Although I saw a few similar threads, I don't believe I saw the specific answer to the following question: For simple linear or multiple linear regression, if your dependent variable is a percentage, ...

15 30 50 per page