search for: obesity

Hi A.K Regarding my question on comparing normal/ obese/overweight with blood pressure change, I did finally as per the first suggestion of stacking the data and creating a normal category . This only gives me a obese not obese 14, but when I did with the wide format hoping to get a obese14,normal14,overweight 14 Vs hibp 21, i could not complete any of the models. This time I classified obese=1

Hi, Sorry, but how did you bring it out? Thanks On Fri, Dec 28, 2012 at 8:48 AM, arun kirshna [via R] < ml-node+s789695n4654093h10@n4.nabble.com> wrote: > Hi, > bp.sub<- structure(list(CODEA = c(1L, 3L, 4L, 7L, 8L, 9L, 10L, 11L, 12L, > 13L, 14L, 16L, 17L), C45 = c(NA, 2L, 2L, 2L, 2L, 1L, NA, 1L, > 1L, 2L, 1L, 2L, 1L), ragek = c(3L, 3L, 3L, 4L, 4L, 3L, 3L, 3L, > 3L, 3L,

...ta in: P. Dalgaard, Introductory Statistics with R, ## 2nd. edition, Springer, 2008 ## logistic regression - example in Dalgaard's Section 13.2, ## page 229 rm(list=ls()) ## data provided on Dalgaard's page 229: no.yes <- c("No","Yes") smoking <- gl(2,1,8,no.yes) obesity <- gl(2,2,8,no.yes) snoring <- gl(2,4,8,no.yes) n.tot <- c(60,17,8,2,187,85,51,23) n.hyp <- c(5,2,1,0,35,13,15,8) d <- data.frame(smoking,obesity,snoring,n.tot,n.hyp) ## d is the data to be analyzed, in table format ## d is the first table on Dalgaard's page 229 ## n.tot = total...

....9 y 1 160 12 5.73 23.11 1 49 25.3 97.2 52 1 2 144 0.01 4.41 28.61 0 55 28.87 2.06 63 1 > dimnames(heart.data$x)[[2]] [1] "sbp" "tobacco" "ldl" "adiposity" "famhist" "typea" [7] "obesity" "alcohol" "age" Note that the printed variable names do not use the column names of the matrix. In contrast, in S-PLUS the names are used; the printout begins: x.sbp x.tobacco x.ldl x.adiposity x.famhist x.typea x.obesity x.alcohol --please do not edit t...

I am trying to figure out how to calculate p-values for the difference in prevalence of a risk factor between men and women. For example, I find that 277 out of 710 male patients and 125 out of 305 female patients have obesity, what is the p-value for their difference? If there is a package that can calculate this in bulk, I would appreciate to learn about it! Thank you [[alternative HTML version deleted]]

Hola a todos, -Estoy estudiando el efecto de dos genotipos (~tratamientos) en la aparición de síndrome metabólico (MetS) con datos longitudinales recogidos a tiempo 0,7,10,15,20 y 25 años. -He hecho un dataframe con las siguientes variables MetS: Síndrome Metabólico (Si=1,No=0) bmi: Indice de masa corporal (IMC) cuando se produce la conversión a MetS+ . Para los que permancen MetS-, esta variable

# Get mean, min, max sigma and skew by group options (digits = 3) library (ISwR data(energy) data %>% group_by(stature) %>% summarize( Mean = mean(expend), Min = min(expend), Max = max(expend), Sigma = sd(expend), Skew = skew(expend)) # Output stature Mean Min Max Sigma Skew <fct> <dbl> <dbl> <dbl> <dbl> <dbl> 1

I'm plotting obesity rates (y-axis) vs Public Health Unit (x-axis) for the province of Ontario and would like to have the Public Health Unit names appear vertically rather than the default, horizontally. I'm actually using the 'barplot2' function in the {gregmisc} library ... I haven't been able to...

...fall and Young's algorithm + resampling into the scheme: lm -> stepAIC -> anova. Actually permcor works fine for me in the case of one regression variable, I need extension for multiple regression models. Any ideas are very much wellcome! Sincerely yours, Serguei Baranov Research "Obesity & Hypertension" MPI of Molecular Genetics, Ihnestr. 73, 14195, Berlin, Germany phone: +49 30 84131238 fax: +49 30 84131228

...97.2 52 1 > 2 144 0.01 4.41 28.61 0 55 28.87 2.06 63 1 > =20 >> dimnames(heart.data$x)[[2]] >> =20 > [1] "sbp" "tobacco" "ldl" "adiposity" "famhist" "typea"= =20 > [7] "obesity" "alcohol" "age" =20 > > Note that the printed variable names do not use the column names > of the matrix. > > In contrast, in S-PLUS the names are used; the printout begins: > x.sbp x.tobacco x.ldl x.adiposity x.famhist x.typea x.obesity x.alc...

Dear all, How to obtain the odds ratio (OR) and 95% confidence interval (CI) with 1 standard deviation (SD) change of a continuous variable in logistic regression? for example, to investigate the risk of obesity for stroke. I choose the happening of stroke (positive) as the dependent variable, and waist circumference as an independent variable. Then I wanna to obtain the OR and 95% CI with 1 SD change of waist circumference.how? Any default package(s) or options in glm available now? if not, how to ca...

I have a function (see below) that does some bootstrapping (I am happy to expand offline why I could use existing functions.) I put my results into and empty matrix and add a row of results with each iteration. My problem is i am a new user to R and I don't understand data frames, matrices, elements, and vectors well. What I would like is to have a data frame I can manipulate outside of the

Hi, I''m really new to rails, so i programmed some stuff and today i read some things about skinny Controllers, fat models. My Controllers are really fat now. So i''m asking myself how can i shrink my controllers and move the code to the models, especially in fact of REST e.g. in focus on error codes? code example: # POST /tasks # POST /tasks.xml def create @authorized

If there are any other users who use AHRQ's SAS code comoanaly2010 and comformat2010 to create comorbidity variables, I thought you might be interested in the following PRELIM code we wrote to mimic its functionality in R. It seems to yield similar results, but may contain errors. Please feel free to comment (kindly) or enhance. I'm sure there are better ways to skin this cat, but we at

I've noticed that R has a number of very useful functions for obtaining descriptive statistics on groups of variables, including summary {stats}, describe {Hmisc}, and describe {psych}, but none that I have found is able to provided weighted descriptives of subsets of a data set (ex. descriptives for both males and females for age, where accurate results require use of sampling

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I apologize if this has been answered. I have researched this to the best of my ability, that's not to say the answer isn't in the archives just I am a new user and I don't know the proper terms to search under. I have an object: f <- mpr100 ~ time + nhb + hispanic + other + rural + hrural + factor(age) + factor(gender) +

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We're running Asterisk 1.8 on a 32-bit Debian machine, and it has been fine for some time now. But! We've got such a incoming call volume over the few weeks that we'll have Asterisk occasionally restart itself. My hunch is that it is in part memory pressure. I can't add RAM and have it help, because it's 32-bit. I intend to move to a 64-bit machine, but I was hoping to