cross-sectional

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Related to Cross-sectional data: Longitudinal data

cross-sec·tion·al

(kros'sek'shŭn-ăl),
1. In histology, a sectioning of a tissue or organ perpendicular to its longitudinal axis.
2. Relating to planar sections of an anatomic or other structure.
See: synchronic.

cross-sectional

Etymology: L, crux + secare, to cut
(in statistics) pertaining to the sampling of a defined population at one point in time, performed in a nonexperimental research design. Compare longitudinal.

cross-sec·tion·al

(kraws sekshŭn-ăl)
Relating to planar sections of an anatomic or other structure.
References in periodicals archive ?
Cross-sectional data generated through biomonitoring studies are based on groups of different individuals sampled at the same time, whereas the longitudinal estimates derived by CoZMoMAN are for single individuals over their entire lifetimes.
For cross-sectional data, users are allowed to choose either the half-normal distribution of inefficiency of Aigner, Lovell, and Schmidt (1977) or the truncated-normal distribution of Stevenson (1980).
NHANES and other cross-sectional data sets can appropriately be used for hypothesis-generating analyses, most appropriately when combined with other information to inform the exploratory analyses.
When cross-sectional data are aggregated, statistical results may be negatively affected due to the loss of variance.
Moreover, the results were based on cross-sectional data and analysis, which most of the time is not relevant to individual brand decisions.
We first extend FLS and SDM by including inflation in a cross-sectional data set of 35-year averages and find, like Levine and Renelt, that inflation is not robust.
So a particular strength of this study was its prospective design, "which overcomes a variety of limitations common to cross-sectional data," Ms.
They explain models for cross-sectional data (including parametric regression models and semiparameter models), univariate U-statistics (including associated models and inference for U-statistics), models for clustered data (including parametric models, distribution-free models and solutions for missing data), multivariate U-statistics (including cross-sectional study designs) and functional response models (including model estimation).
In summary, given we tested a formal model, did not rely totally upon cross-sectional data, and examined the use of specific family-friendly benefits, we believe our study makes a meaningful contribution to the work-family literature.
With these expressions in hand, the authors show that all the structural preference and risk parameters in the model can be identified, even when productivity risk varies over time, given panel data on wages and hours, and cross-sectional data on consumption.
Projection of 3-D Cross-Sectional Data on to 2-Plane:
Cross-sectional data were collected during 2003 using UN process indicators.