similar to: Risk differences with survey package

Hi all- So sorry to bother you all with something pretty basic. I am trying to add the lines method output from svysmooth to a svyplot with style="grayhex". However, the line either appears in the wrong place or if I am running in R Studio it causes the system to crash. I know this is something to do with Lattice graphics, but for the life of me I can not figure out how. Dr. Lumley

I found it easy to use R when typing data manually into it. Now I need to read data from a file, and I get the following errors: > refdata = > read.table("K:\\MerchantData\\RiskModel\\refund_distribution.csv", header > = TRUE) Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : line 1 did not have 42 elements > refdata = >

Hi, I'm trying to compute survey svytable statistic on subsets by using the svyby function. Here is the code: b<-svyby(~V024+V751, by=~V025, design=strat2, svytable, round=TRUE) The vars, V024, V751 and V025 are factors. The by var has 2 levels, and hence there will be two subsets. strat2 is created by the svydesign function. It's giving me the following error: >

svymean w/ svyby is working for me... > svyby(~visitcnt, ~agegrp3.f, svymean, design=svydes) agegrp3.f visitcnt se.visitcnt 18-44 18-44 8.755552 0.4953235 45-64 45-64 10.131555 0.5347806 65+ 65+ 9.588802 0.4323629 svyquantile is working for me... > svyquantile(~visitcnt, quantiles=c(.25, .5, .75), ties="rounded", design=svydes) 0.25

Hello I'm trying to get the proportion "true" for dichotomous variable for various subgroups in a survey. This works fine, but obviously doesn't give proportions directly: svytable(~SurvYear+problem.vandal, seh.dsn, round=TRUE) problem.vandal SurvYear FALSE TRUE 1995 8906 786 1997 17164 2494 1998 17890 1921 1999 18322 1669 2001 17623 2122 ...

Hello, Although my R code for the svymean () and svyquantile () functions works fine, I am stuck with the svyby () and make.formula () functions. I got the following error messages. - Error: object of type 'closure' is not subsettable # svyby () - Error in xx[[1]] : subscript out of bounds # make.formula () A reproducible example is appended below. I would appreciate if

Hi, I’m using the svyby for total statistics, for example: svyby(~p_igov,~div_a,desenho_nps,svytotal,drop.empty.groups=TRUE,vartype =c("se","var","cvpct")) In the numerical variable p_igov (and others) I have many non responses but if I maintain the NA it doesn’t work. summary(base_nps$p_igov) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's

Hello, I'm using a complex survey dataset and my goal is to simply spit out a bunch of probability-weighted outcome variable means for the different levels of covariate. So I first define the structure of the study design (I'm using the CDC's NHANES data): dhanes <- svydesign(id=~PSU, strat=~STRATA, weight=~lab_weight, data=final, nest=TRUE) No problem there. Now I use the

How do I retrieve the replicates estimates from a crosstab done using svyby? Here is an example from the help page for svyby in the package: > data(api) > dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) > rclus1<-as.svrepdesign(dclus1) > > a <- svyby(~api99, ~stype, rclus1, svymean, return.replicates=TRUE) > a$replicates NULL But, compare to > b

Should the svyby function be able to work with svyquantile? I get the error below ... data(api) dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) svyby(~api00, design=dclus1, by = ~stype, quantiles=c(.25,.5,.75), FUN=svyquantile, na.rm=T ) > Error in object$coefficients : $ operator is invalid for atomic vectors A

I am having trouble understanding (i.e. getting) confidence intervals from the survey package. I am using R version 2.8.1 (2008-12-22) and survey package (3.11-2) on FC7 linux. To simplify my question I use an example from that package: R> data(api) R> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) R> (tst <- svyby(~api99, ~stype,

Dear WizaRds, I am struggling to compute correctly a cluster sampling design. I want to do one stage clustering with different parametric changes: Let M be the total number of clusters in the population, and m the number sampled. Let N be the total of elements in the population and n the number sampled. y are the values sampled. This is my example data: clus1 <-

Here is my little scriptlet: optdata = read.csv("K:\\MerchantData\\RiskModel\\AutomatedRiskModel\\soptions.dat", header = FALSE, na.strings="") attach(optdata) library(MASS) setwd("K:\\MerchantData\\RiskModel\\AutomatedRiskModel") for (i in 1:length(V4) ) { x = read.csv(as.character(V4[[i]]), header = FALSE, na.strings=""); y = x[,1]; fp =

I get error trying to run examples from 'svyby' help page (?svyby in package "Survey"): # code data(api) dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) svyby(~api99, ~stype, dclus1, svymean) # error message > Error in match.arg(vartype, several.ok = TRUE) : unused argument(s) (several.ok ...) Is this a version problem? I'm running R

Here is what I tried: optdata = read.csv("K:\\MerchantData\\RiskModel\\AutomatedRiskModel\\soptions.dat", header = FALSE, na.strings="") optdata attach(optdata) for (i in 1:length(V4) ) { x = read.csv(V4[[i]], header = FALSE, na.strings="");x } And here is the outcome (just a few of the 60 records successfully read): > optdata = >

I have a number of files containing anywhere from a few dozen to a few thousand integers, one per record. The statement "refdata18 = read.csv("K:\\MerchantData\\RiskModel\\Capture.Week.18.csv", header = TRUE,na.strings="")" works fine, and if I type refdata18, I get the integers displayed, one value per record (along with a record number). However, when I try "

Dear list, I got some surprising results when using the svytotal routine from the survey package with data containing missing values. Some example code demonstrating the behaviour is included below. I have a stratified sampling design where I want to estimate the total income. In some strata some of the incomes are missing. I want to ignore these missing incomes. I would have expected that

Hi all, When I try the following with pkg Survey it returns the error below: ftable(svyby(~INCOME, ~AGECL+RACECL, svymean, design=q50), rownames=list(AGECL=c("<35", "35-44", "45-54", "55-64", "65-74", ">=75"), RACECL=c("white non hispanic", "non white or

Dear list colleagues, I'm trying to come up with a test question for undergraduates to illustrate comparison of means from a complex survey design. The data for the example looks roughly like this: mytest<-data.frame(harper=rnorm(500, mean=60, sd=1), party=sample(c("BQ", "NDP", "Conservative", "Liberal", "None", NA), size=500,

Hi everyone, my apologies in advance if I'm overlooking something simple in this question. I am trying to use R's survey package to make a direct method age-adjustment to some complex survey data. I have played with postStratify, calibrate, rake, and simply multiplying the base weights by the correct proportions - nothing seems to hit the published numbers on the nose. I am trying to