Transcription of The Basic Two-Level Regression Model
{{id}} {{{paragraph}}}
Example: tourism industry
The Basic Two-Level Regression Model
14:20:25:01:10 Page 11 Page 112 The Basic Two-Level Regression ModelThe multilevel Regression Model has become known in the research literature under avariety of names, such as random coefficient Model (de Leeuw & Kreft, 1986; Long-ford, 1993), variance component Model (Longford, 1987), and hierarchical linearmodel (Raudenbush & Bryk, 1986, 1988). Statistically oriented publications tend torefer to the Model as a mixed-effects or mixed Model (Littell, Milliken, Stroup, &Wo lfinger, 1996). The models described in these publications are not exactly the same,but they are highly similar, and I will refer to them collectively as multilevel regressionmodels . They all assume that there is a hierarchical data set, with one single outcomeor response variable that is measured at the lowest level, and explanatory variables atall existing levels . Conceptually, it is useful to view the multilevel Regression Model as ahierarchical system of Regression equations.
The Basic Two-Level Regression Model
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Related search queries
Chapter 4: Multiple Random, Multiple Random, Random, Chapter, Bias in randomized controlled trials, CHAPTER 5 Ladybug Chase, Flowol 4 Tutorial, F L O W O L 4 T U T O R I A L Chapter, Chapter 4 Management of Wetlands for Wildlife, CHAPTER 3 RESEARCH DESIGN AND METHODOLOGY, CHAPTER 4, Regression analysis with cross-sectional