similar to: svy equivalent of pairwise.t.test

Hello, excuse me if this is trivial. I have some survey data with the following design MyDesign<-(id=ident, weights=~fwgt, fcp=~nval1+nval2, data=hh_data1) I would like to run simple frequency tables such as those provided by the freq() function of rgrs to check the impact of the sampling design on my Ns. Anyway I can do this? thanks, V [[alternative HTML version deleted]]

Dear R users, As a new comer to R, I would like to create a new variable using if statements but don't know how to do it. Basically, I have two variables (EvHint and MinTex). I want to create a third variable called RiskTest. In SPSS, my syntax would look like Compute RiskTest=0. if (EvHint=1 & MinTex=1) RiskTest=1. Question: How do I do this with R? My Data EvHint<-c(0, 0, 0, 1,

Dear list, I am trying to set up a propensity-weighted regression using the survey package. Most of my population is sampled with a sampling probability of one (that is, I have the full population). However, for a subset of the data I have only a 50% sample of the full population. In previous work on the data, I analyzed these data using SAS and STATA. In those packages I used a propensity weight

Hi all, I am running a set of logistic regressions, where we want to use some weights, and I am not sure whether what I am doing is reasonable or not. The dependent variable is turnout in an election - i.e. survey respondents were asked whether or not they voted. The percentage of those who say they voted is much higher than the actual turnout, probably due both to non-response bias and social

hello there, I am trying to use a weight variable in a factor analysis but apparently the factanal command does not have a weight option. Any way to this? Thanks for your suggestions, V [[alternative HTML version deleted]]

Hello, Seeking a way to get the variance inflation factor VIF for a model of regression in complex survey, I have understood that without this package (SURVEY) RGui VIF obtained as follows: fit <- lm(mpg~disp+hp+wt+drat, data=mtcars) vif(fit) But I want to know if survey, Vif is obtained so vif( svyglm(api00~ell+meals+mobility, design=dstrat)) Thank you, happy day

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Dear R-help, I have a question about pairwise.t.test and adjustment for multiple comparisons for paired data points. I have the following data: n=c("x", "x", "x", "x", "x", "x", "x", "x", "x", "x", "y", "y", "y", "y", "y", "y",

Hello forum, I want to find in survey how to test V-cramer and coefficient Goodman-Kruskal gamma, to test the collinearity between varibles to enter a model. For the V-Cramer function is used with the package vcd assocstats but without considering the survey package. I appreciate the cooperation. Att. Diana Martinez [[alternative HTML version deleted]]

Dear all, I am perplexed when trying to get the same results using pairwise.t.test and t.test. I'm using examples in the ISwR library, >attach(red.cell.folate) I can get the same result for pairwise.t.test and t.test when I set the variances to be non-equal, but not when they are assumed to be equal. Can anyone explain the differences, or what I'm doing wrong? Here's an example

# I'm doing a pairwise.t.test on a large dataset and need the output in a data frame so I can work further with it, e.g. so I can export it to a spreadsheet. Is there any way to coerce the results to an exportable format? # For example, if I do: test <- pairwise.t.test(numbers, factors, p.adj="bonferroni") # and then write.table(test, file="output.csv",

Hello, I'm curious if anyone has encounted a version of this problem (and it's solution) involving finding a consistent set of scales for subsets of survey data. The goal is to obtain peoples' rankings of pairwise similarity of a large number of items, on a 1..5 scale for example, and average these across people to use as input to MDS: How similar is object A to B on a 1..5

Hi list-members can anybody tell me why > pairwise.t.test(val, fac) produces an empty p-table. As shown below: Pairwise comparisons using t tests with pooled SD data: val and fac AS AT Fhh Fm Fmk Fmu GBS Gf HFS Hn jAL Kol R_Fill AT - - - - - - - - - - - - - Fhh - - - - - - - - - - - - - Fm - - - - - - -

Hi R users, My question is, If I have 3 groups, A, B, C and I know mean of A =20, B=21, and C=20.5 and I also know the standard error of A =1.1, B=2.2, C=3.2. Plus, I know A has 30 observations, B has 78, C has 45. But I do not have the raw data. Can I use pairwise.t.test to conduct a Bonferroni test? If yes, Could you give me a hint? Thank you so much Chunhao -- View this message in

Hi all, After my reply on R-Help to the relevant thread, I noted what appear to be a couple of typos in the Details section of ?pairwise.t.test. Note text with '**'. Current text: The **pool.SD** switch calculates a common SD for all groups and **used** that for all comparisons (this can be useful if some groups are small). This method does not actually call t.test, so extra arguments

Hi, how can I extract the t-values after running a pairwise.t.test? The output just list the p-values. Many thanks for your help. Cheers Guido ____________________________________ Guido J. Parra School of Tropical Environment Studies and Geography James Cook University Townsville Queensland 4811 Phone: 61 7 47815824 Fax: 61 7 47814020 Mobile: 0437630843 e-mail:

Hi, If I set the p.adjust="none", does it meant that the output p values from the pairwise.t.test will be the same as those from individual t.tests (set var.equal=T, alternative="t")? I actually got different p values from the two tests. See below. Is it supposed to be this way? Thanks Johnny > x [1] 61.6 52.7 61.3 65.2 62.8 63.7 64.8 58.7 44.9 57.0 64.3 55.1 50.0 41.0

pairwise.t.test is returning NAs when one of the samples only has one entry, while TukeyHSD returns results (maybe not trustworthy or believable, but results). I stumbled on this because I did not realize one of my samples only had one entry while most of the others had several hundred, so I realize this is not a desirable situation. I'm really just curious about the difference between how

Hello all, I al trying to join (ADD FILES in SPSS) two files using the rbind() function. However, with rbind() R does not behave the same way as SPSS. I mean, it just concatenates the two blocs with no consideration for same variables if these are not in the same position in the two files. Anyone knows a function that performs the SPSS ADD FILES task? Thanks, V [[alternative HTML version

What's the difference between t.test(x, y) and pairwise.t.test()? Is it just that the former takes two vectors, whereas the latter takes a vector and a factor?