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R Survey package Version 3.16 is current, containing approximately 9000 lines of interpreted R code. (cf 250,000 lines of Fortran for VPLX) Version 2.3 was published in Journal of Statistical Software. Major changes since then are nite population corrections for multistage sampling, calibration and generalized raking, tests

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a weighted hierarchical logistic model using thesvyglm command in the R survey package (Lumley 2011, Lumley 2004). A 2-sample normal approximation binomial test was used to compare the percentage of positive BTV and EHTV results distributed by age at sampling (Fig. 2).

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svyglm does some work related to your design (weights, strata etc) but eventually calls glm. So you should look in ?glm. Basically by specifying family as you do in your example you set down which link function you want to use (which corresponds to "logit" or "probit" etc). A concise explanation is given by Kleiber&Zeileis 2008 (p122).

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Mar 01, 2020 · use of Thomas Lumley’s survey package and in particular svyglm() so we get estimates and standard errors appropriate for the complex survey nature of the data use of the “quasi” family and explicitly chosen link and variance functions to fit my various model structure and interpetability needs

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R is a widely used programming language and software environment for data science. R also provides unparalleled opportunities for analyzing spatial data for spatial modeling. If you have never used R , or if you need a refresher, you should start with our Introduction to R ( pdf )

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(for predict, only possible if they were computed in the svyglm fit) deff. Estimate the design effects. influence. Return influence functions. object. A svyglm object. correlation. Include the correlation matrix of parameters? na.action. Handling of NAs. multicore. Use the multicore package to distribute replicates across processors? df.resid

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