Linked Questions

5
votes
0answers
967 views

Offset in binomial model [duplicate]

My outcomes is binary variable. I would like to perform logistic regression model to estimate the treatment effect of Xs. However, the follow up time was longer for outcomes=1 and shorter when ...
13
votes
2answers
7k views

Binary Models (Probit and Logit) with a Logarithmic Offset

Does anyone have a derivation of how an offset works in binary models like probit and logit? In my problem, the follow-up window can vary in length. Suppose patients get a prophylactic shot as ...
5
votes
1answer
6k views

Difference between: Offset and Weights?

I´d like to know the difference between these parameters when I am using GLM/GLMM/GAMLSS/BETAREG. I have observed a lot of published studies using offset, weights and covariates, however I am not sure ...
5
votes
1answer
10k views

lme4: glmer problems with offset()

this is my first post, so I hope everything is in the right format. I have some problems with glmer and don't know how to fix it, so I hope somebody can help me out with this. I could not find an ...
4
votes
2answers
3k views

How to interpret glm and ols with offset

I ran a few glm and linear models with an offset. Each row in the dataset is a healthcare user. The data contains medical payments and icu days of each user between 2000 to 2007. As the number of ...
4
votes
1answer
557 views

Variable selection in zero-inflation models

I am trying to understand how to perform model comparison between different count models. In this example the author performs a zero-inflated poisson model testing the effect of number of people in a ...
1
vote
0answers
920 views

Probability distribution for right skewed data

My question is very similar to this previous post. I'm searching for the right distribution family to use in a GAM. My data are disease occurrence on benthic organisms (continuous response variable) ...
1
vote
0answers
404 views

specifying random effect as offset in logistic glm (R)

I am working on a measurement error model for presence/absence data using a variant of a Monte Carlo EM (MCEM) algorithm for model fitting. As part of this approach, I simulate random effects by ...
1
vote
1answer
154 views

Questionable diagnostics for a binary logistic model

The model including one binary outcome (0/1; incident rate ~1.2%), one main exposure, and 13 covariates. The whole model is significant and the goodness-of-fit is OK. However, model diagnostic is ...
2
votes
0answers
28 views

Using Offset in Binomial/Logit GLM for Exposure Years? [duplicate]

I am building a GLM Model that predicts whether there will be a claim in a certain policy or not. So target variable is either 0 or 1, so my choice of GLM was Binomial, and link function was Logit. In ...