similar to: Samba LDAP ignores group information

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 all, I have tried to calculate a GLMM fit with lmer (lme4) and glmmPQL (MASS), I also used glm for comparison. I am getting very different results from different functions, and I suspect that the problem is with our dataset rather than the functions, but I would appreciate help in deciding whether my suspicions are right. If indeed we are attempting the wrong type of analysis, some

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

Hello, I am new to R, and I am trying to figure out how to use it for a random effects model. I am using version 2.4.0, and I also have the book Applied Linear Regression by Sanford Weisberg. I have four variables: Swimmer, Sex, Swim, and Difference. Swimmer identifies the number assigned to a particular person. Sex is male/female. Swim identifies the number swim from 1 to 6. Difference

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

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

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

R Experts: I am conducting a meta-analysis where the effect measures to be pooled are simple proportions. For example, consider this data from Fleiss/Levin/Paik's Statistical methods for rates and proportions (2003, p189) on smokers: Study N Event P(Event) 1 86 83 0.965 2 93 90 0.968 3 136 129 0.949 4 82 70 0.854 Total

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:

Forgive my resending this post. To data I have received only one response (thank you Bert Gunter), and I still do not have an answer to my question. Respectfully, John Windows XP R 2.12.1 contrast package. I am trying to understand how to create contrasts for a model that contatains an interaction. I can get contrasts to work for a model without interaction, but not after adding the

Dear Professor Lumley I am relatively new to using R and also to logistic regression. We have analysed our Dudley Health Survey using the survey package. I am now trying to look at associations using svyglm but I am unsure of how to interpret the output and present the resulting model or whether there are any other things I should do to check the validity of the model. Below is an example of

Dear All, I'am looking for examples showing that correlation does not imply causality, the targeted audience consists of undergraduate students (their first year at the university but in the BioMathStat track). All practicals are under R. I was able to extract this from R datasets: ### begin data(sunspots) data(lynx) spots <- window(sunspots, freq = 1, start = 1880, end = 1900) lnx <-

Hi, I am trying to answer the see if density.km (response) is affected by Direction (continuous, integer), Layer (nominal with 12 levels) and direction (nominal with 8 levels). There is an interaction between Layer and Direction. Platform.field is a list of 9 different platforms and is being treated as a random effect. I had previously ran this model without the correlation argument and

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:

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

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 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

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

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")