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In case the origin of heterogeneity can be identified and may be attributed to certain study features, the analysis may be stratified (by considering subgroups of studies, which would then hopefully be more homogeneous), or by extending the analysis to a meta-regression, accounting for (continuous or categorical) moderator variables.
Homogeneity can be studied to several degrees of complexity. For example, considerations of homoscedasticity examine how much the variability of data-values changes throughout a dataset. However, questions of homogeneity apply to all aspects of the statistical distributions, including the location parameter
Homogeneity and heterogeneity; only ' b ' is homogeneous Homogeneity and heterogeneity are concepts relating to the uniformity of a substance, process or image.A homogeneous feature is uniform in composition or character (i.e., color, shape, size, weight, height, distribution, texture, language, income, disease, temperature, radioactivity, architectural design, etc.); one that is heterogeneous ...
Ontology-based data integration involves the use of one or more ontologies to effectively combine data or information from multiple heterogeneous sources. [1] It is one of the multiple data integration approaches and may be classified as Global-As-View (GAV). [ 2 ]
Information integration (II) is the merging of information from heterogeneous sources with differing conceptual, contextual and typographical representations.It is used in data mining and consolidation of data from unstructured or semi-structured resources.
A classic example of heteroscedasticity is that of income versus expenditure on meals. A wealthy person may eat inexpensive food sometimes and expensive food at other times. A poor person will almost always eat inexpensive food. Therefore, people with higher incomes exhibit greater variability in expenditures on food.
Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input. Sensor fusion is also known as (multi-sensor) data fusion and is a subset of information fusion.
The individual reflectance or transmittance of the domains is averaged for micro-heterogeneous samples if the macroscopic reflectance or transmittance is to be calculated. This can be verified simply by investigating, for example, a polycrystalline material under a polarizing microscope having the polarizers crossed: If the crystallites are ...