Search results
Results from the WOW.Com Content Network
They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies (see also Study heterogeneity).
The complementary notion is called heteroscedasticity, also known as heterogeneity of variance. The spellings homos k edasticity and heteros k edasticity are also frequently used. “Skedasticity” comes from the Ancient Greek word “skedánnymi”, meaning “to scatter”.
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 ...
Statistical testing for a non-zero heterogeneity variance is often done based on Cochran's Q [13] or related test procedures. This common procedure however is questionable for several reasons, namely, the low power of such tests [14] especially in the very common case of only few estimates being combined in the analysis, [15] [7] as well as the specification of homogeneity as the null ...
The origins of choice modelling can be traced to Thurstone's research into food preferences in the 1920s and to random utility theory. [4] In economics, random utility theory was then developed by Daniel McFadden [ 5 ] and in mathematical psychology primarily by Duncan Luce and Anthony Marley. [ 6 ]
The endogeneity problem is particularly relevant in the context of time series analysis of causal processes. It is common for some factors within a causal system to be dependent for their value in period t on the values of other factors in the causal system in period t − 1.
Recent research also has reaffirmed that this effect of in-group homogeneity on in-group defining dimensions and out-group homogeneity on out-group defining dimensions may occur because people use their ratings of perceived group variability to express the extent to which social groups possess specific characteristics. [6]
The prevalence of tissue heterogeneity in publicly available gene-expression studies is estimated between 1% and 40%, varying by tissues of origin. [3] Detected tissue heterogeneity may be used to weight samples in differential gene-expression analysis to reduce the impact of the heterogeneity.