Add to ORKGOrganizations are hierarchical in nature. Individuals are subject to various group influences; and this “nesting ” of information creates data analysis problems for researchers interested in drawing conclusions at various levels of analysis. This paper will describe the benefits of multilevel modeling techniques which were designed to handle this hierarchically nested data and will provide resources for conducting multilevel analyses
Information systems (IS) research usually investigates phenomena at one level of analysis at a time....
Researchers in education and many other fields (e.g., psychology, sociology) are frequently confront...
within schools, voters within districts, or workers within firms, to name a few exam-ples. Statistic...
Whenever research is concerned with the analysis of relationships between lowerlevel units (e.g., in...
Empirical analyses of hierarchical data are important in various disciplines, but are most common to...
In this paper, I outline several conceptual and methodological issues related to modeling individual...
Many phenomena in marketing involve multiple levels of theory and analysis. Adopting a multilevel le...
Individuals and the social or organizational groups they belong to can be viewed as a hierarchical ...
Individuals and the social or organizational groups they belong to can be viewed as a hierarchical s...
Analyzing multilevel data: An empirical comparison of parameter estimates of hierarchical linear mod...
Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in ...
Marketing scholars are increasingly recognizing the importance of investigating phenomena at multipl...
textDue to the inherently hierarchical nature of many natural phenomena, data collected rests in ne...
The data collected in order to test the research questions in social sciences usually have multileve...
The multilevel models allow to analyse the data variation simultaneously at the different levels1. A...
Information systems (IS) research usually investigates phenomena at one level of analysis at a time....
Researchers in education and many other fields (e.g., psychology, sociology) are frequently confront...
within schools, voters within districts, or workers within firms, to name a few exam-ples. Statistic...
Whenever research is concerned with the analysis of relationships between lowerlevel units (e.g., in...
Empirical analyses of hierarchical data are important in various disciplines, but are most common to...
In this paper, I outline several conceptual and methodological issues related to modeling individual...
Many phenomena in marketing involve multiple levels of theory and analysis. Adopting a multilevel le...
Individuals and the social or organizational groups they belong to can be viewed as a hierarchical ...
Individuals and the social or organizational groups they belong to can be viewed as a hierarchical s...
Analyzing multilevel data: An empirical comparison of parameter estimates of hierarchical linear mod...
Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in ...
Marketing scholars are increasingly recognizing the importance of investigating phenomena at multipl...
textDue to the inherently hierarchical nature of many natural phenomena, data collected rests in ne...
The data collected in order to test the research questions in social sciences usually have multileve...
The multilevel models allow to analyse the data variation simultaneously at the different levels1. A...
Information systems (IS) research usually investigates phenomena at one level of analysis at a time....
Researchers in education and many other fields (e.g., psychology, sociology) are frequently confront...
within schools, voters within districts, or workers within firms, to name a few exam-ples. Statistic...