View source: R/svyglmParallel.R
svyglmParallel | R Documentation |
This is a non-user function that is managed by RegParallel, the primary function.
svyglmParallel(
data,
design,
formula.list,
FUN,
variables,
terms,
startIndex,
blocksize,
blocks,
APPLYFUN,
conflevel,
excludeTerms,
excludeIntercept)
data |
A data-frame that contains all model terms to be tested. Variables that have all zeros will, automatically, be removed. REQUIRED. |
design |
A survey design, created by survey::svydesign. REQUIRED. |
formula.list |
A list containing formulae that can be coerced to formula class via as.formula(). REQUIRED. |
FUN |
Regression function. Must be of form, for example: function(formula, data) glm(formula = formula, family = binomial, data = data). REQUIRED. |
variables |
Vector of variable names in data to be tested independently. Each variable will have its own formula in formula.list. REQUIRED. |
terms |
Vector of terms used in the formulae in formula.list, excluding the primary variable of interest. REQUIRED. |
startIndex |
Starting column index in data object from which processing can commence. REQUIRED. |
blocksize |
Number of variables to test in each foreach loop. REQUIRED. |
blocks |
Total number of blocks required to complete analysis. REQUIRED. |
APPLYFUN |
The apply function to be used within each block during processing. Will be one of: 'mclapply(...)', system=linux/mac and nestedParallel=TRUE; 'parLapply(cl, ...)', system=windows and nestedParallel=TRUE; 'lapply(...)', nestedParallel=FALSE. REQUIRED. |
conflevel |
Confidence level for calculating odds or hazard ratios. REQUIRED. |
excludeTerms |
Remove these terms from the final output. These will simply be grepped out. REQUIRED. |
excludeIntercept |
Remove intercept terms from the final output. REQUIRED. |
This is a non-user function that is managed by RegParallel, the primary function.
A data.table
object.
Kevin Blighe <kevin@clinicalbioinformatics.co.uk>
require(survey)
data(nhanes)
design <- svydesign(id = ~ SDMVPSU,
strata = ~ SDMVSTRA,
weights = ~ WTMEC2YR,
nest = TRUE,
data = nhanes)
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