search for: raced

Colleagues, I am in the process of learning R. I've been able to import my dataset (from Stata) and do some simple coding. I have now come to coding situation that requires some assistance. This is some code in SPSS that I would like to be able to execute in R: if (race eq 1 and usborn=0) confused=1 . if (race eq 2 and usborn=0) confused=1 . if (race eq 1 and usborn=1) confused=0 . if (race

Hi to anyone who is willing to help, I have a csv. file which has 1999 horses as the rows and the age(in years) of the horse at each race as columns. Ive read this file into R and called it 'horses'. Im trying to find the longest break between each race in the horse's first year of racing. I already have a numeric called 'age.first' which is the age at which each horse had its

Hello, We have a publication in ASPLOS 2012 that uses the LLVM infrastructure. Is it possible to add this to the publications web page: http://llvm.org/pubs/ ? Publication: Data Races vs. Data Race Bugs: Telling the Difference with Portend Link: http://dl.acm.org/citation.cfm?id=2150997 Abstract: Even though most data races are harmless, the harmful ones are at the heart of some of the worst

Hi, I am trying a linear regression model where the dependent variable is the size of the heart corrected for the patient's height and weight. This is labelled as LAVI. The independent variables are race (european or non-eurpoean), age, sex (male or female) of the patient and whether they have diabetes and high blood pressure. sample size 2000 patients selected from a community. when I

This test has been broken for a while. It is meant to test that when the appliance cachedir is empty, two simultaneous runs of libguestfs (both rebuilding the full appliance) will not cause conflicts, because (eg) the locking in either supermin or libguestfs is not working. However the test only set $TMPDIR, but the ./run script sets $LIBGUESTFS_CACHEDIR which overrides $TMPDIR, so it was simply

I have a large dataset where each Subject answered seven similar Items, which are binary yes/no questions. So I've always used Subject and Item random effects in my models, fit with lmer(), e.g.: model<-lmer(Response~Race+Gender+...+(1|Subject_ID)+(1| Item_ID),data,binomial) But I recently realized something. Most of the variables that I've tested as fixed effects are properties

ThreadSanitizer [1] pointed out that in the nbd plugin, nbd_close() can attempt close() in the main thread while the worker thread is still attempting to start a read(). Normally, if the read() loses the race, it will get a harmless EBADF that exits the worker thread (which is what we want, as we are closing the connection anyway); but if another connection happens to start in that window, we

Hi Jake, About a year ago in commit 5049c3422d26b2b68877307c41b35d7e6aae3235, you attempted to solve a race in llvm-objcopy. What was the race? I ask because unless "last change wins" is the result you want, then the race isn't solved. The problem is that `sys::fs::rename` is just a thin wrapper around POSIX semantics, and replacing an existing file is not an error. Dave

On Mon, Mar 19, 2012 at 4:30 PM, Chris Lattner <clattner at apple.com> wrote: > > On Mar 19, 2012, at 2:52 PM, Kostya Serebryany wrote: > > Hello, > > While instrumenting LLVM IR in ThreadSanitizer (race detector), I need > to distinguish between a store to vtable pointer (vptr) and any other > regular store. > This special treatment should be limited to class

Hello I believe that I'm getting very close in my modeling application. I've come across a challenge that I am unable to solve and would really appreciate the group's opinion. I've been using the val.prob function from the Design library (Thanks Frank!!) to both evaluate and visualize my model. From the scores and graph, it appears as my model is very accurate in

Hi folks, I have five imputed data sets and would like to apply the same recoding routines to each. I could do this sort of thing pretty easily in Stata using MIM, but I've decided to go cold turkey on other stats packages as a incentive for learning more about R. Most of the recoding is for nominal variables, like race, religion, urbanicity, and the like. So, for example, to recode race

There is a race condition between XEN_DOMCTL_SHADOW_OP_ENABLE_LOGDIRTY and HVMOP_track_dirty_vram hypercall. Although HVMOP_track_dirty_vram is called many times from qemu-dm which is connected via VNC, XEN_DOMCTL_SHADOW_OP_ENABLE_LOGDIRTY is called only once from a migration process (e.g. xc_save, libxl-save-helper). So the race seldom happens, but the following cases are possible.

Hi, I'm not sure of the correct nomenclature or function for what I'm trying to do. I'm interested in calculated a logistic regression on a binary dependent variable (True,False). There are a few ways to easily do this in R. Both SVM and GLM work easily. The part that I want to add is "group wise" awareness. So that the algorithm computes the coefficients to maximize

Hello, While instrumenting LLVM IR in ThreadSanitizer (race detector), I need to distinguish between a store to vtable pointer (vptr) and any other regular store. This special treatment should be limited to class DTORs, so I should also know when a function is a DTOR. Rationale: need to distinguish benign and harmful races on vptr (

What''s the standard way to prevent race conditions in controllers? Say user has many posts. Post controller has action add_post that receives user id, post controller find()s the user and while he is creating the post entry an administrator deletes that user in a separate session. We cannot assume the database checks foreign key integrity. How do you get that right? -- fxn

I'm uncertain if this is perhaps a stupid question: I want to create "centered" dummy variables to use in a call to glm(), and wondering if there's some slick method in R to do so. That is, rather than have a factor, which results in a glm() fit returning coefficients specifying either absence or presence of the factor, I'd like to fit a glm() without intercept such that

I have been trying to use lavaan (version 0.4-7) for a simple path model, but the program seems to be computing far less degrees of freedom for my model then it should have. I have 7 variables, which should give (7)(8)/2 = 28 covariances, and hence 28 DF. The model seems to only think I have 13 DF. The code to reproduce the problem is below. Have I done something wrong, or is this something I

I have a data set with seven inputs. Four of which are categorical. For my midterm, my professor wants us to scale all the inputs. This means, I pressume, that I have to use 'recode' or 'factor' to transform the categorical data in numerical. For example, one input variable is 'race=(b,w,h,o)'. I just want to assign a numerical value to all 'b,w,h,o'. I

Hello: I have an lme object, say lme_res2, which was generated using the varIdent. I'm trying to extract the double 1.532940 from the object, but I can't find it by attributes(lme_res2) or attributes(summary(lme_res2)). How can I pull it out (so that I can save it to another variable)? Thanks. Shin Linear mixed-effects model fit by REML Data: dat Log-restricted-likelihood:

I just started using R and I'm having all sorts of "fun" trying different things. I'm going to document the different things I'm doing here as a kind of case study. I'm hoping that I'll get help from the community so that I can use R properly. Anyways, in this study, I have demographic data, drug usage data, and side effect data. All of this is loaded into a csv