Semiparametric mixed model analysis benefits from variability estimates such as standard errors of effect estimates and variability bars to accompany curve estimates. We show how the underlying variance calculations can be done extremely efficiently compared with the direct naïve approach. These streamlined calculations are linear in the number of subjects, representing a two orders of magnitude improvement. Copyright © 2007 John Wiley & Sons, Ltd
Several pharmacological studies involve experiments aimed at testing for a difference between experi...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom this pap...
The coefficient of determination is well defined for linear models and its extension is long wanted ...
Semiparametric mixed model analysis benefits from variability estimates such as standard errors of e...
In linear mixed models the influence of covariates is restricted to a strictly parametric form. With...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
First, to test the existence of random effects in semiparametric mixed models (SMMs) under only mome...
Linear mixed effects methods for the analysis of longitudinal data provide a convenient framework fo...
Repeated measures design (or longitudinal study) are commonly seen in many research fields, especial...
This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as ...
In small samples it is well known that the standard methods for estimating variance components in a ...
Standard statistical decision-making tools, such as inference, confidence intervals and forecasting,...
Non-linear relationships are accommodated in a regression model using smoothing functions. Interact...
Mixed effect models have become very popular, especially for the analysis of longitudinal data. One ...
Several pharmacological studies involve experiments aimed at testing for a difference between experi...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom this pap...
The coefficient of determination is well defined for linear models and its extension is long wanted ...
Semiparametric mixed model analysis benefits from variability estimates such as standard errors of e...
In linear mixed models the influence of covariates is restricted to a strictly parametric form. With...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
First, to test the existence of random effects in semiparametric mixed models (SMMs) under only mome...
Linear mixed effects methods for the analysis of longitudinal data provide a convenient framework fo...
Repeated measures design (or longitudinal study) are commonly seen in many research fields, especial...
This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as ...
In small samples it is well known that the standard methods for estimating variance components in a ...
Standard statistical decision-making tools, such as inference, confidence intervals and forecasting,...
Non-linear relationships are accommodated in a regression model using smoothing functions. Interact...
Mixed effect models have become very popular, especially for the analysis of longitudinal data. One ...
Several pharmacological studies involve experiments aimed at testing for a difference between experi...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom this pap...
The coefficient of determination is well defined for linear models and its extension is long wanted ...