A fixed effects approach to GLMs with clustered data
نویسنده
چکیده
In situations where a large data set is partitioned into many relatively small groups, and you want to test for group differences, the number of parameters tend to increase with sample size. This fact causes the standard assumptions underlying asymptotic results to be violated. There are (at least) two possible solutions to the problem, first, a random intercepts model, and second, a fixed effects model, where asymptotics are replaced by a simple form of bootstrapping. In the glmML package, both these approaches are implemented. In this paper, only the fixed effects approach is considered.
منابع مشابه
On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs
Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we s...
متن کاملActuarial Statistics With Generalized Linear Mixed Models
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh & Nelder (1989). Traditional GLMs however model a sample of independent random variables. Since actuaries very often have repeated measurements or longitudinal data (i.e. repeated measurements over time)...
متن کاملApplications of Generalized Linear Mixed Models in Actuarial Statistics
Over the last decade the use of generalized linear models (GLMs) in modelling actuarial data received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh & Nelder (1989). Standard GLMs however model a sample of independent random variables. Since actuaries very often have repeated measurements or longitudinal data (i.e. repeated measurements over time...
متن کاملGeneralized Linear Mixed Models
Generalized linear models (GLMs) represent a class of fixed effects regression models for several types of dependent variables (i.e., continuous, dichotomous, counts). McCullagh and Nelder [32] describe these in great detail and indicate that the term ‘generalized linear model’ is due to Nelder and Wedderburn [35] who described how a collection of seemingly disparate statistical techniques coul...
متن کاملEstimated estimating equations: Semiparametric inference for clustered/longitudinal data
We introduce a flexible marginal modelling approach for statistical inference for clustered/longitudinal data under minimal assumptions. This estimated estimating equations (EEE) approach is semiparametric and the proposed models are fitted by quasi-likelihood regression, where the unknown marginal means are a function of the fixed-effects linear predictor with unknown smooth link, and variance...
متن کامل