Questions tagged [generalized-linear-model]
A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)
8 questions from the last 30 days
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Can an estimated marginal mean be used to calculate an effect size for a power analysis?
I'm interested in calculating the required sample size for detecting a future hypothetical 30% increase in a marginal mean from a model based on pilot data (accounting for covariates and random ...
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Weighted quantile sum (WQS) and Cox model
I am working on weighted quantile sum (WQS), and I know that the WQS index obtained represents the effect of the mixture on my outcome.
In order to know which effect the mixture has on my outcome in ...
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Interpreting the predicted values from family = poisson(link="log") , binary outcome
I am fitting a simple model for dataset where the outcome is binary (1 or 0).
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GLMM (Gamma, log link) shows effect not visible in raw data — why does the model detect it?
I’m analyzing within-subject reaction-time data (4 conditions × 2 positions A × 2 positions B).
RTs are positive and skewed, so I used a Gamma GLMM with a log link:
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How to choose features for a Gamma regression, vs. Linear Regression
I'm new to using GLMs which are not Linear Regression, and am working on a project where I am using Gamma regression with a log-link. I'm having problems with the feature engineering step.
With linear ...
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How to test whether the addition of a random intercept is statistically significant from a glmer() model to glm()
I'm getting back into mixed effects models and have forgotten a lot. I know this is a doable test for linear regression but have forgotten if there is an equivalent for logistic regression. If I have ...
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Penalising intercept in a Poisson GLM? - offset present
I am running a Poisson GLM on insurance claim data. I use L1/L2 regularisation to account for potential lack of full credibility in my dataset. I also have an industry table, which (log of it) I use ...
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lm() and glm() equivalence for log-transformed response variable [duplicate]
I can't seem to wrap my head around this:
What is the glm() equivalent for lm(log(y) ~ x1 + x2, data=data)?
Is it?
a. ...
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