Alternative Ways of Analyzing Hierarchical Data
There are several alternative ways of analyzing hierarchical data, although most of them have some problems. First, traditional statistical techniques can be used. One could disaggregate higher-order variables to the individual level, and thus conduct an analysis on this individual level (for example, assign class variables to the individual level). The problem with this approach is that it would violate the assumption of independence, and thus could bias our results. This is known as atomistic fallacy. Another way to analyze the data using traditional statistical approaches is to aggregate individual level variables to higher-order variables and then to conduct an analysis on this higher level. The problem with this approach is that it discards all within-group information (because it takes the average of the individual level variables). As much as 80-90% of the variance could be wasted, and the relationship between aggregated variables is inflated, and thus distorted. This is known as ecological fallacy, and statistically, this type of analysis results in decreased power in addition to the loss of information.
Another way to analyze hierarchical data would be through a random-coefficients model. This model assumes that each group has a different regression model - with its own intercept and slope. Because groups are sampled, the model assumes that the intercepts and slopes are also randomly sampled from a population of group intercepts and slopes. This allows for an analysis in which one can assume that slopes are fixed but intercepts are allowed to vary. However this presents a problem, as individual components are independent but group components are independent between groups, but dependent within groups. This also allows for an analysis in which the slopes are random; however, the corrrelations of the error terms (disturbances) are dependent on the values of the individual-level variables. Thus, the problem with using a random-coefficients model in order to analyze hierarchical data is that is still not possible to incorporate higher order variables.
Read more about this topic: Multilevel Model
Famous quotes containing the words alternative, ways, analyzing, hierarchical and/or data:
“A mental disease has swept the planet: banalization.... Presented with the alternative of love or a garbage disposal unit, young people of all countries have chosen the garbage disposal unit.”
—Ivan Chtcheglov (b. 1934)
“Children treat their friends differently than they treat the other people in their lives. A friendship is a place for experimenting with new ways of handling anger and aggression. It is an arena for practicing reciprocity, testing assertiveness, and searching for compromise in ways children would not try with parents or siblings.”
—Lawrence Kutner (20th century)
“Color is my day-long obsession, joy and torment. To such an extent indeed that one day, finding myself at the deathbed of a woman who had been and still was very dear to me, I caught myself in the act of focusing on her temples and automatically analyzing the succession of appropriately graded colors which death was imposing on her motionless face.”
—Claude Monet (1840–1926)
“Authority is the spiritual dimension of power because it depends upon faith in a system of meaning that decrees the necessity of the hierarchical order and so provides for the unity of imperative control.”
—Shoshana Zuboff (b. 1951)
“This city is neither a jungle nor the moon.... In long shot: a cosmic smudge, a conglomerate of bleeding energies. Close up, it is a fairly legible printed circuit, a transistorized labyrinth of beastly tracks, a data bank for asthmatic voice-prints.”
—Susan Sontag (b. 1933)