schisto: Schistosomiasis Data Set
In multiPIM: Variable Importance Analysis with Population Intervention Models
Description
Usage
Format
Source
Description
Data on types of water exposure and schistosomiasis infection.
Usage
1
Format
A data frame containing the outcome variable (stoolpos – 1 = positive stool sample (infected), 0 = negative stool sample), 7 water contact exposure variables (total time subject spent doing each activity: laundry, tool washing, bathing, swimming, ditch digging, rice planting, fishing), and two categorical covariates (village id number and age category).
Note: Village label does not correspond to the id numbers from the paper.
Source
Spear RC, Seto E, Liang S, Birkner M, Hubbard A, Qiu D, Yang C, Zhong B, Xu F, Gu X, Davis GM (2004). "Factors Influencing the Transmission of Schistosoma Japonicum in the Mountains of Sichuan Province of China." The American Journal of Tropical Medicine and Hygiene, 70(1), 48-56.
multiPIM documentation built on May 1, 2019, 8:07 p.m.
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Description Usage Format Source
Description
Data on types of water exposure and schistosomiasis infection.
Usage
1 |
Format
A data frame containing the outcome variable (stoolpos – 1 = positive stool sample (infected), 0 = negative stool sample), 7 water contact exposure variables (total time subject spent doing each activity: laundry, tool washing, bathing, swimming, ditch digging, rice planting, fishing), and two categorical covariates (village id number and age category).
Note: Village label does not correspond to the id numbers from the paper.
Source
Spear RC, Seto E, Liang S, Birkner M, Hubbard A, Qiu D, Yang C, Zhong B, Xu F, Gu X, Davis GM (2004). "Factors Influencing the Transmission of Schistosoma Japonicum in the Mountains of Sichuan Province of China." The American Journal of Tropical Medicine and Hygiene, 70(1), 48-56.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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