summary.mdr
(Package: MDR) :
Summarizing the results of an MDR model
summary method for class 'mdr', after fitting with mdr.cv or mdr.3WS
● Data Source:
CranContrib
● Keywords:
● Alias: summary.mdr
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0 images
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predict.mdr
(Package: MDR) :
MDR model predictions
method for class 'mdr' to predict case/control status for new data using a previously fit MDR model.
● Data Source:
CranContrib
● Keywords:
● Alias: predict.mdr
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0 images
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plot.mdr
(Package: MDR) :
Plotting the results of an MDR model
a method for class 'mdr' to plot case/control counts for each factor combination of a previously fit MDR model
● Data Source:
CranContrib
● Keywords:
● Alias: plot.mdr
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1 images
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permute.mdr
(Package: MDR) :
Function to perform a permutation test after fitting an MDR model
After fitting an object of class 'mdr', performs a permutation test to assess the statistical significance of the balanced accuracy evaluation measure of the 'best model'.
● Data Source:
CranContrib
● Keywords:
● Alias: permute.mdr
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0 images
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mdr
(Package: MDR) :
Function to perform MDR on a dataset for a given set of loci
Determines the top x MDR models over a specified set of combinations of loci which minimize balanced accuracy (mean of sensitivity and specificity). Ideally, should be used in conjunction with an internal validation method, such as cross-validation (mdr.cv) or a three-way split (mdr.3WS).
● Data Source:
CranContrib
● Keywords:
● Alias: mdr
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0 images
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mdr.hr
(Package: MDR) :
Function to estimate the accuracy of an MDR model given high-risk/low-risk status of genotype combinations
Determines the balanced accuracy (mean of sensitivity and specificity) of an MDR model (specified combination of loci and high-risk/low-risk genotype combinations) which minimize balanced accuracy. Is used to determine prediction error estimates in cross-validation (mdr.cv).
● Data Source:
CranContrib
● Keywords:
● Alias: mdr.hr
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0 images
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mdr.cv
(Package: MDR) :
A function to perform MDR on a dataset using k-fold cross-validation for internal validation.
Determines the best MDR model up to a specified size of interaction K by minimizing balanced accuracy (mean of sensitivity and specificity), while using a k-fold cross-validation internal validation method. The function mdr.cv is essentially a wrapper for the function mdr.
● Data Source:
CranContrib
● Keywords:
● Alias: mdr.cv
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1 images
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mdr.ca.adj
(Package: MDR) :
Function to calculate a post-hoc adjusted prediction estimate of classification accuracy, corrected for prospective data with previously estimated population prevalence
After fitting an object of class 'mdr' and obtaining a best model, calculate an adjusted estimate of classification accuracy to be used for prediction that accounts for retrospective sampling and incorporates disease prevalence, as implemented in Winham and Motsinger-Reif 2010.
● Data Source:
CranContrib
● Keywords:
● Alias: mdr.ca.adj
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0 images
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mdr.3WS
(Package: MDR) :
A function to perform MDR on a dataset using the three-way split for internal validation.
Determines the best MDR model up to a specified size of interaction K by minimizing balanced accuracy (arithmetic mean of sensitivity and specificity), while using a three-way split internal validation method. The three-way split randomly separates the data into training, testing, and validation sets. The function mdr.3WS is essentially a wrapper for the function mdr.
● Data Source:
CranContrib
● Keywords:
● Alias: mdr.3WS
●
1 images
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Performs multifactor dimensionality reduction (MDR) to detect potential gene-gene interactions in case-control studies, using balanced accuracy as an evaluation measure to rank potential models. Offers both cross-validation (CV) and a three-way split as internal validation methods to prevent over-fitting, as well as permutation testing and post-hoc prediction estimates.
● Data Source:
CranContrib
● Keywords:
● Alias: MDR, MDR-package
●
0 images
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