Sentence examples for lack of dataset from inspiring English sources

The lack of dataset uniformity poses substantial challenges to initiatives seeking to assess the quality of healthcare systems [ 11].

Likewise, the test of the predictive hazard equations (that include cohort factors) on an independent data set could not be implemented due to the lack of dataset with comparable cohort information or adequate structure that would minimize the risk of confounding between factors.

Empirical testing and verification of the predictions of these theoretical models has greatly lagged the theoretical literature due to a lack of datasets with both information on network structure and socio-economic outcomes of interest.

One of the main reasons for the scarcity of evidence on the impact of refugee experiences on schooling is the lack of datasets that include a large sample of individuals who experienced international displacement and their contemporaries who did not, so that the educational outcomes of both groups can be compared.

In some ways this represents a classic chicken-and-egg problem as the lack of datasets inhibits the development of methods, and the lack of suitable methods makes the collection of adequate datasets a risky and expensive endeavour.

While these methods for estimating times have found widespread acceptance and use, it has been difficult to assess their reliability because of the lack of datasets where the true time of interest is known.

The lack of datasets to adequately assess land use intensity and changes therein is particularly apparent at the global scale, where existing data on land use intensity are either coarse in scale (e.g. national-scale statistics) or connected to considerable uncertainties [ 5,6 ], or both.

Producing information about the socio-demographic characteristics of individuals living in different urban-rural areas, the practices serving them and relevant health outcomes is currently not straightforward because of the lack of a dataset that contains everything.

However, we were unable to test if pCR predictors are of great value for HER2-positive and Basal-like patients survival outcomes due to the lack of a dataset that included outcomes, neoadjuvant response and microarray data.

In addition, Design Patterns recovery techniques can be used for the creation of datasets of Design Patterns for which the lack of such datasets is a known problem at the current stage of this work.

However, the lack of large datasets has hampered the development of such algorithms.