Search results for "categorical data"
showing 4 items of 4 documents
Categorical versus geometric morphometric approaches to characterizing the evolution of morphological disparity in Osteostraci (Vertebrata, stem Gnat…
2020
Morphological variation (disparity) tends to be evaluated through two non-mutually exclusive approaches: (i) quantitatively, through geometric morphometrics, and (ii) in terms of discrete, ‘cladistic’, or categorical characters. Uncertainty over the comparability of these approaches diminishes the potential to obtain nomothetic insights into the evolution of morphological disparity, and the few benchmarking studies conducted so far show contrasting results. Here, we apply both approaches to characterising morphology in the stem-gnathostome vertebrate clade Osteostraci, in order to assess congruence between these alternative methods as well as to explore the evolutionary patterns of the grou…
An Overview of Collapsibility
2004
Collapsing over variables is a necessary procedure in much empirical research. Consequences are yet not always properly evaluated. In this paper, different definitions of collapsibility (simple, strict, strong, etc.) and corresponding necessary and sufficient conditions are reviewed and evaluated. We point out the relevance and limitations of the main contributions within a unifying interpretative framework. We deem such work to be useful since the debate on the topic has often developed in terms that are neither focused nor clear.
Parceling in Multilevel Structural Equation Models for the measure of a latent construct
2019
When the variables of interest are measured by a set of items on units having a multilevel setting, conventional structural equation models cannot be used because the assumption of independence of all latent variables and indicators across units is violated due to the within-cluster dependence. In this work we propose the use of parcelling in defining of latent variables of a multilevel structural equation model (MSEM). The paper aims to face the problem of the use of categorical item response data when a multilevel SEM must be applied.
Item Response Trees: a recommended method for analyzing categorical data in behavioral studies
2015
Behavioral data are notable for presenting challenges to their statistical analysis, often due to the difficulties in measuring behavior on a quantitative scale. Instead, a range of qualitative alternative responses is recorded. These can often be understood as the outcome of a sequence of binary decisions. For example, faced by a predator, an individual may decide to flee or stay. If it stays, it may decide to freeze or display a threat and if it displays a threat, it may choose from several alternative forms of display. Here we argue that instead of being analyzed using traditional nonparametric statistics or a series of separate analyses split by response categories, this kind of data ca…