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Matter of factly, it can be shown that data splitting into a training set and an external test set often estimates the prediction error less precise than proper cross-validation.
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None of the results of the survey are shown — that data is not revealed at the household level, and aggregate data won't be made available for several months.
It is shown that data for maximum pit depths can be separated into those with Gumbel statistics and those for which a Frechet distribution is more appropriate.
Averaged R time, K time, Angle and Coagulation Index (CI) of Cell-BAL treated pigs (± SEM, n = 13); where no error bars are shown, that data point does not have replicates, due to occasional technical issues with blood sample analyses.
It is shown that data on disease transmission in part of the community enables the estimation of central parameters and it is possible to compute the sample size required to make inferences with a desired precision.
Likewise, it has been shown that data quality issues are common in data warehouses and electronic patient records [ 34- 36].
It has been shown that data linkage quality can have an overall impact on research outcomes, potentially biasing results [ 27].
It has been shown that data mining of relevant data sets can successfully lead to the identification of biologically interesting targets [ 15, 16, 58- 67].
Although there is ongoing debate regarding the reliability of self-reports of alcohol consumption, it has been shown that data thus collected are a valid source of information in the case of dependent individuals [ 18].
Despite all preprocessing, it has been shown that data generated in different labs or on different microarray platforms or on different generations of the same platform may not be comparable due to platform or lab specific biases [ 8].
It has been shown that online data collection increases response rates and data quality [ 39].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com