This study applies the multilevel analysis technique to longitudinal data of a large clinical trial. The technique accounts for the correlation at different levels when modeling repeated blood pressure measurements taken throughout the trial. This modeling allows for closer inspection of the remaining correlation and non-homogeneity of variance in the data. Three methods of modeling the correlation were compared
Data from clinical trials investigating on-demand medication often consist of an intentionally varyi...
Multilevel modelling facilitates the analysis of hierarchical data where observations may be nested ...
repeated measures, growth curve analysis, longitudinal data, multilevel analysis, hierarchical linea...
This study applies the multilevel analysis technique to longitudinal data of a large clinical trial....
Abstract Background The data arising from a longitudi...
Many benefits can be gained if multi-factorial diseases with a high incidence and prevalence are bet...
Abstract Purpose This paper aims to discuss multilevel modeling for longitudinal data, clarifying ...
Novel imaging techniques are playing an increasingly important role in drug development, providing i...
Background: In clinical setting, to answer a research question, very often more than one outcome var...
A substantial part of medical education research focuses on learning in teams (e.g., departments, pr...
<p><b>Copyright information:</b></p><p>Taken from "Multilevel modeling for the analysis of longitudi...
Longitudinal data arise when individuals are measured several times during an ob- servation period a...
Many studies in biostatistics deal with binary data. Some of these studies involve correlated observ...
Data from clinical trials investigating on-demand medication often consist of an intentionally varyi...
The hierarchical linear model in a linear model with nested random coefficients, fruitfully used for...
Data from clinical trials investigating on-demand medication often consist of an intentionally varyi...
Multilevel modelling facilitates the analysis of hierarchical data where observations may be nested ...
repeated measures, growth curve analysis, longitudinal data, multilevel analysis, hierarchical linea...
This study applies the multilevel analysis technique to longitudinal data of a large clinical trial....
Abstract Background The data arising from a longitudi...
Many benefits can be gained if multi-factorial diseases with a high incidence and prevalence are bet...
Abstract Purpose This paper aims to discuss multilevel modeling for longitudinal data, clarifying ...
Novel imaging techniques are playing an increasingly important role in drug development, providing i...
Background: In clinical setting, to answer a research question, very often more than one outcome var...
A substantial part of medical education research focuses on learning in teams (e.g., departments, pr...
<p><b>Copyright information:</b></p><p>Taken from "Multilevel modeling for the analysis of longitudi...
Longitudinal data arise when individuals are measured several times during an ob- servation period a...
Many studies in biostatistics deal with binary data. Some of these studies involve correlated observ...
Data from clinical trials investigating on-demand medication often consist of an intentionally varyi...
The hierarchical linear model in a linear model with nested random coefficients, fruitfully used for...
Data from clinical trials investigating on-demand medication often consist of an intentionally varyi...
Multilevel modelling facilitates the analysis of hierarchical data where observations may be nested ...
repeated measures, growth curve analysis, longitudinal data, multilevel analysis, hierarchical linea...
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