The phrase "absence data as" is not correct in written English and seems incomplete.
It may be intended to introduce a comparison or a description of how absence data is used or categorized.
Example: "The report analyzed absence data as a key indicator of employee engagement."
Alternatives: "absence information as" or "absence records as".
This study is the first, to our knowledge, to use actual sickness absence data as opposed to self-reported data, for both self-certified and GP-certified sickness absence, and to match this with data on individual attitudes.
The possible use of administrative sickness absence data as a risk marker of future sickness absence and disability pension was demonstrated in a Danish study [ 37].
To determine the value of routinely collecting worker absence data as part of this kind of surveillance and to assess a threshold level of possible alert cases, directors of six major Italian hospitals were asked for the number of cases that fit the alert definition in 2003.
In addition, epidemiological data on childhood TB is limited [ 4] mainly because of absence of surveillance data as well as poor ascertainment of cases [ 6].
Furthermore, given that we must assume that it has not yet achieved environmental equilibrium, using methods that rely on (pseudo) absence data, such as generalized linear models or generalized additive models, is problematic (Guisan and Thuiller 2005).
These presence / absence data were used as input for multivariate analyses: NMDS, cluster analysis and CCA.
On the other hand, the sickness absence data were accurate and consistent, as they were obtained from company records.
However, data entry was blinded, as sickness absence data were extracted from the company records automatically in electronic format and computer entry of self-reported data was done by a research assistant who was blinded to group assignments.
Further studies are needed to validate the LEAPS against external and objective measures of work performance, such as employer work absence data and objective measures of productivity.
Functional metrics based on presence-absence data, such as functional richness, may be more sensitive to identifying changes in the exploitation of comparatively rare functions among different catch groupings29.
In recent comparisons among several techniques of algorithms and predictions of species distributions, MaxEnt ranked as the best-performing model using presence-only data and showed a better performance comparable to 16 other algorithms, including several traditional tools using presence-absence data, such as general linear models (GLM) and general additive models (GAM) [69].
