similar to: goodness of fit for logistic regression with survey package

I have survey data that I am working on. I need to make some multi-way tables and regression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster

Hello, My question likely got buried so I am reposting it in the hopes that someone has an answer. I have thought more about the question and modified my question. I hope tha my specific question is: I am attempting to create a bootstrap procedure for a finite sample using the theory of Rao and Wu, JASA (1988) that replicates within each strata (h) n_h - 1 times. To this end, I require a

I've installed the openss* rpm's from metalab.unc.edu/pub/Linux/distributions/redhat/contrib/libc6/i386 on a redhat 6.2 system. sshd is running but refuses all connections from all hosts including localhost. The client reports debug: Connection established. ssh_exchange_identification: Connection closed by remote host debug: Calling cleanup 0x8056160(0x0)

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 All I am trying to include sampling weights in multilavel regression analysis using packege lme4 using following codes print(fm1 &lt;- lmer(DC~sex+age+smoker+alcohol+fruits(1|setting), dataset,REML = FALSE), corr = FALSE) print(fm2 &lt;- lmer(DC~sex+age+smoker+alcohol+fruits(1|setting), dataset,REML = FALSE), corr = FALSE,weights=sweight) The problem is both the

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

On 30 April 2020 at 16:40, Samuele Carcagno wrote: | after some further investigation I found out that the issue was related | to some calls to the `solve` function in `make.rgb`, and indeed running | `example(solve)` would hang my R session. After I changed the default | BLAS with: | | sudo update-alternatives --config libblas.so.3-x86_64-linux-gnu | | the problem disappeared. The BLAS

Here is my model with interaction terms and control variables (I changed variables names for easy read): reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are discrete ordinal variables; but I will treat them as continuous variables. (a) How can I see the predicted values of y for each of these scenarios (210

On 08/05/2016 01:36 PM, Stuart D. Gathman wrote: > On Fri, 5 Aug 2016, Marco Walther wrote: > >> On 08/03/2016 05:25 AM, Stuart Gathman wrote: >>> I've made some progress getting this Tripplite to work: >>> http://gathman.org/2016/07/30/Standard_Schmandard/ >>> >>> Basically, plug it into a USB hub that actually implements USB2.0,

Greetings, I have a very, very, simple research question. I want to predict one dichotomous variable using another dichotomous variable. Straightforward, right? The issue is that the dataset has two issues causing some complications for me. 1) The subjects are not independent -- they are sibling pairs. Every person in the dataset has a sibling in the dataset. This needs to be treated a

On 08/05/2016 03:03 PM, Marco Walther wrote: > On 08/05/2016 01:36 PM, Stuart D. Gathman wrote: >> On Fri, 5 Aug 2016, Marco Walther wrote: >> >>> On 08/03/2016 05:25 AM, Stuart Gathman wrote: >>>> I've made some progress getting this Tripplite to work: >>>> http://gathman.org/2016/07/30/Standard_Schmandard/ >>>> >>>>

Il 30/04/20 03:39, Dirk Eddelbuettel ha scritto: > > On 30 April 2020 at 03:26, Samuele Carcagno wrote: > | I'm not familiar with the internals of `viridisLite`, so I'm not sure > | I'd be able to help there. I could open a bug report on the > | `viridisLite` repo and see if the author has suggestions on how to > | narrow down the issue. > > It would help if

On Fri, 5 Aug 2016, Marco Walther wrote: > On 08/03/2016 05:25 AM, Stuart Gathman wrote: >> I've made some progress getting this Tripplite to work: >> http://gathman.org/2016/07/30/Standard_Schmandard/ >> >> Basically, plug it into a USB hub that actually implements USB2.0, then >> power cycle the port when it hangs. It does seem to be a hardware >>

Hi, I've written some code that fetches data from an Access Database (2003), processes the data, then saves the modified data back into a table in the Access database. It works if I only pass through the code once, but if I put a loop around the code so that I fetch data from a different source table, and then save it again to a different destination table, the code crashes. It is

Hi, I'm configuring samba-3.0.2a-Debian. I have it configured with LDAP. I get samba decline access for a W98 clinet when using user authentication (NT domain), and the following entries get into /var/log/smb/machine.log: -------------------------------------------------------------------- [2004/05/07 13:46:07, 3] smbd/sesssetup.c:reply_sesssetup_and_X(772) Domain=[WORKGROUP]

I?d like to solicit some advice on a debugging problem I have in the quantreg package. Kurt and Brian have reported to me that on Debian machines with gfortran 9 library(quantreg) f = summary(rq(foodexp ~ income, data = engel, tau = 1:4/5)) plot(f) fails because summary() produces bogus estimates of the coefficient bounds. This example has been around in my R package from the earliest days of R,

Hi All, is there any chance of vectorising the two ifelse() statements in the following code: for(i in gp){ new[i,1] = ifelse(srow[i]>0, new[srow[i],zippo[i]], sample(1:100, 1, prob =Y1, rep = T)) new[i,2] = ifelse(drow[i]>0, new[drow[i]>0,zappo[i]], sample(1:100, 1, prob =Y1, rep = T)) } Where I am forced to check if the value of drow and srow are >0 for each line... in

I have a big dataset. I want to create a new factor variable with certain conditions based on two existing numeric variables. Existing variables: indinc (range: 0 to 16), groupinc (range -3 to 5) Conditional values that 'incorp' will take: If groupinc = 5, then ?cons?; If groupinc is -3 : -2, AND indinc < 9, then ?ethnat?; If groupinc is -2 : -1, AND indinc > 8, then ?civic?; If

Hi all, I have setup samba / openldap as describes by the idealx howto and as such I am using the smbldap-tools. However, I would like to add the givenname and email address fields for all users. What is the best way to do this? I would prefer continuing to use the smbldap-tools, but I cannot seem to find a good way to do this. When I try to: $ smbldap-usermod -M testuser@testdomain.net

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