Sentence examples for large proportions of data from inspiring English sources

Exact(1)

As can be readily seen, even with large proportions of data missing, all three methods perform equally well with only marginal differences, a fact that was also observed for sNMF and ADMIXTURE in Frichot et al. (2014).

Similar(59)

25, 26 A large proportion of data was missing for race (40%) and tumor stage (~70%) in the EMR records.

Dietary sodium intake was included in exploratory models (results were very similar), but not included in final models because a large proportion of data was missing.

Although such approximations worked well even with limited number of patients [ 11], it does not take into account BLD data and hence could underestimate the standard error when a large proportion of data are BLD.

The approach used here allows us to capture and visualize the complexity of these relationships in high dimensional data, rendering large proportions of the data available for analysis.

Consequently, surveys involving obtaining parental SES information from adolescents have resulted in large proportions of missing data (Currie et al. 1997; Molcho et al. 2007; Wardle et al. 2004).

Seventh, we had relatively large proportions of missing data for several variables.

It is apparent that the model can accurately predict small and large proportions of missing data, but is less accurate at predicting moderate proportions.

However, constituents such as nickel and vanadium often have large proportions of daily data below monitor detection limits (Burnett et al. 2000) and, therefore, may pose additional challenges to analysis.

Other studies have reported seasonal patterns in PM2.5 and its associations with hospitalizations (Bell et al. 2008; Ito et al. 2011), but the limited time frame of our data set, and the larger proportion of data collected during the winter than in the summer, prohibited extensive analysis by season.

However, the exposure estimation accuracy may also decrease if the data uncertainty resulting from the large proportion of missing data or biased aggregated data is large, which is the case of ozone estimation at long time scales.

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