search for: smokering

Hi. Excuse my English. I've installed Samba+OpenLDAP as a PDC. Everything works fine but Samba ignores completely group information. Linux is ok. Any clue? I'm going crazy here! Here's the sittuation: user: fish1 home dir: /home/reaml/swim/fish1 primary group: swimmers other groups: smokers Directory of smoker's group: /home/realm/smokers Here's an 'ls -l' on

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

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

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:

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

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

Dear UseRs, Suppose I have data regarding smoking habits of a prospective cohort and wish to determine the risk ratio of colorectal cancer in the smokers compared to the non-smokers. What do I do at the end of the study with people who die of heart disease? Can I just censor them exactly the same as people who become uncontactable or who die in a plane crash? If not, why not? I'm thinking

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

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

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, 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

I'm having some problems getting CentOS to serve up my Smokeping pages ( http://oss.oetiker.ch/smokeping/) However, I'm having problems getting the pages to serve up correctly. Here is a quick run down of what I've done. (1) wget and untar to /usr/local/smokeping (2) chown -R root:root /usr/local/smokeping (3) modifying to the following files to reflect my environment (not sure if

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

Hello, The following code is expected to produce 4 charts. But, I only get charts 1,2 ,& 4, NOT CHART # 3. For Chart# 3, I am getting the following error message: Error in tapply(1:NROW(x), list(factor(strata)), function(index) { : arguments must have same length I would appreciate if someone could help me resolve the issue. Thanks, Pradip # BELOW IS THE REPRODUCIBLE EXAMPLE setwd

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",

Hi, Does anyone know if: with R can you take a set of numbers and aggregate them like you can in SPSS? For example, could you calculate the percentage of people who smoke based on a dataset like the following: smoke = 1 non-smoke = 2 variable 1 1 1 2 2 1 1 1 2 2 2 2 2 2 When aggregated, SPSS can tell you what percentage of persons are smokers based on the frequency of 1's and 2's. Can

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

Hi, i am trying to read a .txt file, do a couple of select if statements on my data, and then finally use the ?table function to get frequency counts on the data. Specifically, i am looking at answering the following question: What is the frequency of Grade 7 students in the province of Alberta who are smokers? I am having some problems: 1)i cannot get the column names to show up when print

Hi, I've written code to extact a pumf file in R, subset it, and weight it like you would do in SPSS. My code is below & it works great. My question is: how do i then calculate the frequencies of smokers (1) versus non-smokers (2) after having weighted my file? or even the process that SPSS is going through to aggregate the data? Thanks, Nat Here is my code: