similar to: Using SPSS Labels

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 obtain within-group correlations on a subset of variables. I first selected my variables using the following command: mydata$x<-mydata[c("iq","education","achievement")] I'd like to look at correlations among those variables separately for men and women. My gender variable in mydata is coded 1 (women) and 0 (men). I have successfully used

Hi all, I got curious about something, so in proper scientific fashion I obtained some data and analyzed it. Question: what is the female participation in the R-help email list? Data: the most recent list postings, obtained from the website. I took my best shot at classifying the names given in the email header as male/female, but ended with a fair number of unknowns. This dataset had 2797

I have an app that has two models -- products and details. I''m building a form that allows a user to create a new product and specify a description, etc. The form needs to allow for creation of multiple items in the details model/table. for example, I have a block of form items that collect info for the men''s version of the product -- inventory count for each size, etc. And

Suppose we have the following data set: Men Women Dieting 10 30 Non-dieting 5 60 If I run the Fisher exact test in R then what does alternative = greater (or less) imply? For example: mat = matrix(c(10,5,30,60), 2,2) fisher.test(mat,alternative ="greater") I get the p-value = 0.01588 and odds ratio = 3.943534. Also, when I flip the rows of

I've been playing around with various table tools, trying to construct a fairly simple cross-tab. It shouldn't be hard, but for some reason it turning out to be (for me). If I want to see how many men and how many women agree with a agree/disagree question (coded 1,0), I can do this: >attach(mydata) >mytable <- table(male, q1.bin) # gender and a binary response variable

Hello, I have a problem with selecting the right type of sums of squares for an ANCOVA for my specific experimental data and hypotheses. I do have a basic understanding of the differences between Type-I, II, and III SSs, have read about the principle of marginality, and read Venable's "Exegeses on Linear Models" (http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf). I am pretty new to

Hi useRs, Many studies of the link between red meat and colorectal cancer use Cox proportional hazards with (among other things) a gender covariate. If it is true that men eat more red meat, drink more alcohol and smoke more than women, and if it is also true that alcohol and tobacco are known risk factors then why does it make sense to "adjust" for gender? I would think that in this

Dear all R users, I got a strange problem while working with SPSS data : I wrote following : library(foreign) data.original = as.data.frame(read.spss(file="c:/Program Files/SPSS/Employee data.sav")) data = as.data.frame(cbind(data.original$MINORITY, data.original$EDUC, data.original$PREVEXP, data.original$JOBCAT, data.original$GENDER)) colnames(data) = c('MINORITY',

Is there an easy way to make graphs for the following data. I have pretest and posttest scores for men and women. I would like to form a 'titlted segment' plot for the data. That is, make segments joining the scores, with different types of segments for men and women. Example data: menpre <- c(43,42,26,39,60,60,46) menpost <- c(40,41,36,42,54,58,43) womenpre <-

v 2.0.1 (sooooh old!) on Win2k I think I know the answer to this but I can hope ... I have data for continuous variables (measures of residents) by a categorical variable in range (1,22), the units in which they live. I want to plot these data with a pair of boxplots one above another with same x-axis (1,22) using par(mfrow=c(2,1)) and then plotting first for the women then for the men.

Hi, I have a SPSS datafile which is used for my textbook in the statistics (and which is available on http://abacon.com/fox/s6720p2.sav, but it is originally from ICPSR). When I opened it with SPSS 10 and run Frequencies on it I have got 979 valid data a 27 missing. However, see below (unfortunately, I have used R in preparation of my homework, which caused me an error on this): >

Dear List, I am working on a stats project and have been stumped by the issue of replacing values in a column conditional on values from a different column. I searched the forum and google in general, and was able to put some code together, but it's not working the way it's supposed to... I appreciate any help you can offer! A detailed description of the issue, and the code I came up

Hi, I want to use my some session data when I validate som data in the model. The specific problem I have is that I present different forms data based on gender, and then dependent of the gender, there''s different fields that needs validation. I''m wondering what''s the preffered way of doing this. The session data is not present in the model, i.e: class Myclass

Didn''t know what else to call this subject, sorry. Anyway this is more a general discovery question then a coding one. Is it possible (and I already know it should be) to create forms where depending on a particular choice in one select tag, one or another select tags would be presented in the form. As an example, a shopping site , where a dropdown has options of: 1-Men''s shoes

I have been trying to specify a different color palette to the image method in plot.Design. My model has crossed two rcs() arguments and one two-level gender argument. The goal which appears to have been mostly achieved is to produce separate bivariate plots for men and women The call to plot does produce a level plot but it appears only with the default color palette despite various

Dear R-helpers, I'm not a speciallist in writing complex functions, and the function still very rusty (any kind of suggestions are very welcome). I want to implement Gale-Shapley algorithm for R Language. It is based on http://www.jstor.org/stable/10.2307/2312726 Gale and Shapley (1962) , and it has evolved to

Using the weight argument with a variance function in lme (nlme), you can allow for heteroscedasticity of the within-group error. Is there a way to do this for the other variance components? For example, suppose you had subjects, days nested within subjects, and visits nested within days within subjects (a fully nested two-way design) and you had, say men and women subjects. Could you allow for

Hello samba, I would like an advice on following: is there any way how to tell samba what transfer mode to use? I think I read that samba does only binary and to use text you have to use something else. We have windows machines using text files on linux samba server and i need to transfer those files in text mode. Can anyone help me please? -- Best regards, Martin

On 12/24/18 7:21 AM, vsnsdualce at memeware.net wrote: > Debian is not ruled by the men who actually write the software, but > instead women. *snip* Can we please ban the person who sent that disgusting rant to the list?