Characterization and analytical techniques are methods used to identify, isolate or quantify chemicals or materials, or to characterize their physical properties. They include microscopy, light or radiation scattering, spectroscopy, calorimetry, chromatography, gravimetric and other measurements used in chemistry and materials science.
Used when data are nested. Nested data occur when several individuals belong to the same group under study. For example, in child care research, many children are cared for by the same child care provider and many child care providers work within the same state. The children are nested in the child care provider and the child care provider is nested in the state Allows researchers to determine the effects of characteristics for each level of nested data, child care providers and states, on the outcome variables
Used to estimate the length of a status or process. For example, in child care policy research, duration models have been used to estimate the length of time that families receive child care subsidies.
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Grouping methods are techniques for classifying observations into meaningful categories. One grouping method, discriminant analysis, identifies characteristics that distinguish between groups. For example, a researcher could use discriminant analysis to determine which characteristics identify families that seek child care subsidies and which identify families that do not.
Allows researchers to examine multiple direct and indirect causes of a dependent, or outcome, variable.
A path diagram is created that identifies the routes between the independent and dependent variables The paths can run directly from an independent variable to a dependent variable, or they can run indirectly from an independent variable, through an intermediary variable, to the dependent variable The entire model is tested to determine the relative importance of each causal pathway