similar to: sampling weights in package lme4

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

Hi, We are seeing a frequent assertion failure on LMTP delivery with 2.3.0. This only appears to happen on CentOS/RHEL 7. Jan 24 08:30:58 smoker-devautomerge-c7-1 dovecot: lmtp(29540): Panic: file lib-event.c: line 148 (event_unref): assertion failed: (event != current_global_event) Jan 24 08:30:58 smoker-devautomerge-c7-1 dovecot: lmtp(29540): Error: Raw backtrace:

How do I change the font size in the facet labels along the edges of the plot? For example (from the ggplot help file): p<-ggplot(tips, sex ~ smoker, aesthetics=list(x=tip/total_bill)) gghistogram(p) In this plot, the facet labels are "smoker: No", "smoker: Yes", "sex: Female", "sex: Male". What command can I use to reduce the font size of

I apologize in advance if this is posted all ready I have not been able to find any information about it. I have this data frame and I want to sort smoking by retlevel. Age Gender BMI Calories Fat Fiber Alc retlevel Smoking 1 64 Female 18.87834 1828.0 63.4 14.7 0.0 Normal Non-Smoker 2 25 Female 20.64102 1517.4 59.1 5.9 0.0 Normal Smoker 3

hy Hope everyone is fine, I have one issue coming in asterisk , What i am doing is i am generating a callback if some one calls at a specif access number on asterisk, Asterisk sends a busy signal to the calling party that he received a request from party and then sends the call back to the person from where asterisk received a request but in From field as you can see below astrisk is sending the

Hi Aki, Please see below: Thank you -Nick # gdb /usr/libexec/dovecot/lmtp ./3445 Using host libthread_db library "/lib64/libthread_db.so.1". Core was generated by `dovecot/lmtp'. Program terminated with signal 6, Aborted. #0 0x00007f297814d1f7 in raise () from /lib64/libc.so.6 Missing separate debuginfos, use: debuginfo-install dovecot-2.3.0-8.cp1162.x86_64 (gdb) back #0

Hi Guys, I am trying to add a Broadcom Physical NIC to a virtual Machine as Passthrough device. However I am getting following error. Error starting domain: unsupported configuration: host doesn't support passthrough of host PCI devices Traceback (most recent call last): File "/usr/share/virt-manager/virtManager/asyncjob.py", line 88, in cb_wrapper

Hi, we are trying to do structural equation modelling on R. However, one of our predictor variables is categorical (smoker/nonsmoker). Now, if we want to run the sem() command (from the sem library), we need to specify a covariance matrix (cov). However, Pearson's correlation does not work on the dichotomous variable, so instead we produced a covariance matrix using the Spearman's (or

This is probably very simple but I'm new to R so apologies for being stupid. I have some data with No coded as 0 and yes coded as 1. e.g. id sex alcohol smoker 1 M 0 1 2 F 1 0 3 M 0 0 I realise I can covert the numerical variable back to a factor by falcohol<-factor(alcohol,levels=0:1) levels<-c("No","Yes")

Hi everyone, I have a certain number of samples and I want to visualize the groups those samples belong to. For example, suppose to have three variables, age, sex, and smoker/nonsmoker, and three samples, S1, S2, S3. S1 is 35, male, nonsmoker S2 is 24, female, nonsmoker S3 is 24, female, smoker at the end I have the following data frame: S1 S2 S3 age 35 24 30 sex M F F smk N N S What I

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

I still need to do some repetitive statistical analysis on some outcomes from a dataset. Take the following as an example; id sex hiv age famsize bmi resprate 1 M Pos 23 2 16 15 2 F Neg 24 5 18 14 3 F Pos 56 14 23 24 4 F Pos 67 3 33 31 5 M Neg 34 2 21 23 I want to know if there are statistically detectable differences in all of the continuous variables in

Hello there, I have two groups (men and women) and I know per group how many of them smoke or don't smoke (women 40 of 200; men 100 of 300). I would like to know how I can compare in R if men and women differ significantly in their smoking. However, because there are more men in the sample than women I cannot just compare the number of smokers and non-smokers in both groups, right?! (I would

I'm trying to do a Hosmer-Lemeshow 'goodness of fit' test on my logistic regression model. I found some code here: http://sas-and-r.blogspot.com/2010/09/example-87-hosmer-and-lemeshow-goodness.html The R code is above is a little complicated for me but I'm having trouble with my answer: Hosmer-Lemeshow: p=0.6163585 le Cessie and Houwelingen test (Design library): p=0.2843620

Full_Name: Sven Sandin Version: 2.0.0 OS: SuSE Linux 9.0 Submission from: (NULL) (81.227.17.135) Have just compiled and installed R-2.0.0.tar.gz running SuSE9.0. The function vcov do not accept "coxph" object as input any longer. The same R-program running R1.9.1 do work. R-program attached below. Exporting the coxph object from R2.0.0 to R1.9.1 I get vcov ouput in R1.9.1. Exporting

I am making exploratory analyses on a complex survey data by using survey package. Could you help me how to see the goodness of fit for the model below? Should I use AIC, BIC, ROC, or what? What code would let me run a goodness of fit test for the model? Here are my codes: #incorporating design effects# > mydesign <- svydesign(id=~clust, strata=~strat, weights=~sweight, > data=mydata)

Hi! This is a bug in the new event code. Can you get a full gdb backtrace? Aki > On January 27, 2018 at 6:58 AM "J. Nick Koston" <nick at cpanel.net> wrote: > > > Hi, > > We are seeing a frequent assertion failure on LMTP delivery with 2.3.0. This only appears to happen on CentOS/RHEL 7. > > Jan 24 08:30:58 smoker-devautomerge-c7-1 dovecot:

I wanted to add a convenience method on my User class to see if he was already signed up for a tournament. Here''s my spec context "A User signed up for one tournament" do setup do @t1 = Tournament.new @t1.save false @t2 = Tournament.new @t2.save false @user = User.new @user.save false @user.registrations << Registration.new(:tournament =>

Any suggestions on the following would be grateful. I'm trying to impute data, where a fictitional dataset is defined as... set.seed(110) n <- 500 test <- data.frame(smoke_status = rbinom(n, 2, 0.6), smoke_amount = rbinom(n, 2, 0.5), rf1 = rnorm(n), rf2 = rnorm(n), outcome = rbinom(n, 1, 0.3)) # smoke_status (0, 1, 2) is c("non-smoker, "ex-smoker",