Sentence examples for more robust dataset from inspiring English sources

The present study is a retrospective, descriptive study that examines whether open-source data can be used in conjunction with official data to create a more robust dataset on jail suicides.

Expanding upon the current data collection process would enable researchers to create a more robust dataset, enrich the overall quality of the variables collected, and allow for a more nuanced understanding of the correlates of jail suicide.

However, these results have been criticised due to methodological constraints on collection of testes size data, and a smaller more robust dataset did not find this relationship [45].

However, detailed scenarios for the historical biogeography of Bauhinia and its relatives still need more robust dataset from palaeobotany and molecular phylogeny in future research.

This study offers some benefits not found in other RNA-sequencing studies, including that we sequenced the RNA from a diverse group of different subjects and demonstrated trends across subject groups, and we enriched the RNA to remove many ribosomal and human RNAs to characterize a more robust dataset.

This pattern confirms the trend previously suggested by microarray analysis [ 24], and represents a more robust dataset from which to make such observations: unlike the previous experiment, which involved hybridizing non-human samples to a human-specific microarray, these qRT-PCR results are not confounded by sequence mismatches between sample and microarray chip.

Although the increased risk ratio for rosiglitazone compared with other diabetes medications has been demonstrated in more robust clinical datasets with adequate longitudinal records of patients (21), the current study provides two novel and important insights.

Also the gene classification will become more robust as the dataset will grow.

While Relief uses, for each individual, a single nearest neighbor in each class, ReliefF, a variant of Relief, uses multiple nearest neighbors, and thus is more robust when the dataset contains noise [ 18].

The results suggested that while the spatial structure was usually non-robust to the tested methodological options when working with the original dataset, it became more robust for the transformed datasets (especially for the log-backtransformed dataset).

Moreover, the recent changes in precipitation regimes bring to another issue in rainfall thresholds analysis: on one hand, statistical analyses are more robust if a long dataset is used and, according to the basic principles of statistics, the longest available time series should be used.