similar to: R Included with Open Infrastructure for Outcomes (OIO) system

> Announcing the initial release of RSessionDA. > > RSessionDA provides objects for interacting with R from Zope > <www.zope.org>, a full-featured web application development system. These > objects permit evaluation of functions in the R language using information > in Zope. R data objects, graphics files, printed output, script > transcripts, and data files can be

> Announcing the initial release of RSessionDA. > > RSessionDA provides objects for interacting with R from Zope > <www.zope.org>, a full-featured web application development system. These > objects permit evaluation of functions in the R language using information > in Zope. R data objects, graphics files, printed output, script > transcripts, and data files can be

This is the named article: http://ije.oxfordjournals.org/content/37/5/1161.long maybe it can help you to help me... :-( -- View this message in context: http://r.789695.n4.nabble.com/INSTRUMENTAL-VARIABLES-WITH-BINARY-OUTCOMES-tp4642361p4642363.html Sent from the R help mailing list archive at Nabble.com.

Hi, I am simulating an event that has 15 possible outcomes and I have a vector 'pout' that gives me the probability of each outcome - different outcomes have different probabilities. Does anyone know a simple way of simulating the outcome of my event? If my event had only two possible outcomes (0/1) I would pick a uniform random number between 0 and 1 and use it to choose between the two

Hello, In a study exploring transgenerational transmission of anxiety disorder we investigate whether infants react to experimentally induced mood changes of their mothers. We measured the time that an infant needed to cross a cliff (=crossing time) depending on whether his mother had previously undergone a mood induction (treatment) or not (control). The treatment is thus a

I have been using generalized linear models in SPSS 18, in order to build models and to calculate the P values. When I was building models in Excel (using the intercept and Bs from SPSS), I noticed that the graphs differed from my expectations. When I ran the dataset again in R, I got totally different outcomes for both the P values as well as the Bs and the intercepts. The outcomes of R seem much

I will like to analyse a binary cross over design using the random effects model. The probability of success is assumed to be logistic. Suppose as an example, we have 4 subjects undergoing a crossover design, where the outcome is either success or failure. The first two subjects receive treatment "A" first followed by treatment "B". The remaining two subjects receive

Dear List, I have two questions about how to do predictions using lrm, specifically how to predict the ordinal response for each observation *individually*. I'm very new to cumulative odds models, so my apologies if my questions are too basic. I have a dataset with 4000 observations. Each observation consists of an ordinal outcome y (i.e., rating of a stimulus with four possible

Good Afternoon I have noticed results similar to the following several times as I have used R over the past several years. My .csv file has a header row and 3073 rows of data. > rskreg<-read.table('D:/data/riskregions.csv',header=T,sep=",") > dim(rskreg) [1] 2722 13 > rskreg<-read.csv('D:/data/riskregions.csv',header=T) > dim(rskreg) [1] 3073

Dear List: I have searched the archives and my R books and cannot find a method to transform a continuous variable into a binary variable. For example, I have test score data along a continuous scale. I want to create a new variable in my dataset that is 1=above a cutpoint (or passed the test) and 0=otherwise. My instinct tells me that this will require a combination of the transform

Dear All, I wonder if there is an efficient way to fit the generalized linear mixed model for multivariate outcomes. More specifically, Suppose that for a given subject i and at a given time j we observe a multivariate outcome Yij = (Y_ij1, Y_ij2, ..., Y_ijK). where Y_ijk is a binomial(n_ijk, p_ijk). One way to jointly model the data is to use the following specification: g(p_ijk) =

Given this example #start code a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) wilcox.test(a, b, paired=FALSE) #sum of rank for first sample sum.rank.a <-

I have justed upgraded R v1.7.0 on Windows NT 4 and have installed the latest RMySQL (version 0.5-1)and DBI (version 0.1-5) packages. When I issue the following commands (tactfully adjusted) R just crashes and disappears, any ideas? require(RMySQL) m <- dbDriver("MySQL") con <- dbConnect(m, dbname="xxx", user="xxx", password="xxx",

> -----Original Message----- > From: Warnes, Gregory R > Sent: Friday, January 16, 2004 3:52 AM > To: 'r-packages'; 'python-announce '; 'rsoap-talk'; 'Dan Nathan'; 'RPy > List' > Subject: Announce: RPy version 0.3.3 > > > RPy Version 0.3.3 is now available from the RPy home page at > http://rpy.sf.net. > > What

> -----Original Message----- > From: Warnes, Gregory R > Sent: Friday, January 16, 2004 3:52 AM > To: 'r-packages'; 'python-announce '; 'rsoap-talk'; 'Dan Nathan'; 'RPy > List' > Subject: Announce: RPy version 0.3.3 > > > RPy Version 0.3.3 is now available from the RPy home page at > http://rpy.sf.net. > > What

hi, i have this in my code Article.find_by_contents("#{searchstring} +city:#{passedincity}") well that returns to me only articles that belong to whatever the user selected in city. now is it possible to search the grandparent? for example class country has_many states class states has_many cities belongs_to country class city belongs_to states ...... i would like to search

Dear R Users, I would like to use R to fit a Weighted Least Square model for a binary outcome, say Y. The model is the one widely used for a binary dependent variable when the logistic model has not been proposed. Does anyone know how to specify the weight as the square root of 1/(E(Y)(1-E(Y)) in lm() or any other regression functions? I know that varPower() in the package of gls() can provide

Hi! I'm pretty raw when working with the R models (linear or not). I'm wondering has anybody worked with the NLME library and dichotomous outcomes. I have a binary outcome variable that I woul like to model in a nested (multilevel) model. I started to fit a logistic model to a NLS function, but could not suceed. I know there are better ways to do it in R with either the LRM or GLM wih

Hi there Within sampleSelection, I'm trying to calculate the marginal effects for variables that are present in both the selection and outcome models. For example, age might have a positive effect on probability of selection, but then a negative effect on the outcome variable. i.e. Model<-selection(participation~age, frequency~age, ...) Documentation elsewhere describes one method for

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