Data Quality Visualization Tools for Partially Accruing Data

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Description

Package for visualizing data quality of partially accruing data.

Details

Package: accrued
Type: Package
Version: 1.4.1
Date: 2016-06-07
License: GPL-3

Author(s)

Julie Eaton (jreaton@uw.edu) and Ian Painter

References

[1] Painter I, Eaton J, Olson D, Revere D, Lober W. How good is your data. In conference abstracts for the International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance. Emerging Health Threats Journal. 2011;4. (http://www.eht-journal.net/index.php/ehtj/article/view/11907)

[2] Painter I, Eaton J, Olson D, Lober W, Revere D. (2011). Visualizing data quality: tools and views. In conference abstracts for the International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance. Emerging Health Threats Journal. 2011;4. (http://www.eht-journal.net/index.php/ehtj/article/view/11907)

[3] Lober W, Reeder B, Painter I, Revere D, Bugni P, McReynolds J, Goldov K, Webster E, Olson D. Technical Description of the Distribute Project: A Community-based Syndromic Surveillance System Implementation. Online Journal of Public Health Informatics. 2014;5(3). (http://dx.doi.org/10.5210/ojphi.v5i3.4938)

[4] J. Eaton, I. Painter, D. Olson, W. Lober. Visualizing the quality of partially accruing data for use in decision making. Online Journal of Public Health Informatics. 2015;7(3). (http://dx.doi.org/10.5210/ojphi.v7i3.6096)

Examples

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data(accruedDataExample)
testData <- data.accrued(accruedDataExample)
plot(testData)
summary(testData)
plot(summary(testData))
uploadPattern(testData)
laggedTSarray(testData, lags=c(1,3,5,7) )
lagHistogram(testData)
summary(accruedErrors(testData))
plot(accruedErrors(testData))
currentValues = asOf(testData, currentDate=20)
# plot(currentValues)

data(accruedDataILIExample)
testData2 <- data.accrued(accruedDataILIExample)
plot(accruedErrors(testData, testData2))