Displaying 20 results from an estimated 45 matches for "se2".
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2011 Mar 18
1
Problem with Slope.test function
.....
Is it correct to use t-test in this situation and how to compute df for it? My solution is:
s1<-coefficients(summary(lm(fitted(m1)~d1$R)))[2,1] #Slopes of regr.line
s2<-coefficients(summary(lm(fitted(m2)~d2$R)))[2,1]
se1<-coefficients(summary(lm(fitted(m1)~d1$R)))[2,2] #SE of slopes
se2<-coefficients(summary(lm(fitted(m2)~d1$R)))[2,2]
df1<-df.residual(lm(fitted(m1)~d1$R)) #D. of f.
df2<-df.residual(lm(fitted(m2)~d1$R))
kk<-function(se1,se2,df1,df2){(se1^2+se2^2)^2/(se1^4/(df1-1)+se2^4/(df2-1))} #D. of f. for Welsch test
tt<-function(s1,s2,se1,se2){(s1-s2)/sqrt(se1^...
2010 Oct 21
1
gam plots and seWithMean
...pars<-f2$coef
pars2<-pars[5:13]
pars2<-as.matrix(pars2,9,1)
pars2
points(d,premat2%*%pars2,cex=0.5,col=rgb(0,0.6,0.3,0.2))
#premat2%*%pars2 = cdif
#confidence intervals when seWithMean = FALSE
devAskNewPage(ask=T)
plot(f2)
points(d,cdif,cex=0.5,col=rgb(0,1,0,0.2))
Vp2<-f2$Vp[5:13,5:13]
se2<-sqrt(diag(premat2%*%Vp2%*%t(premat2)))
points(d,cdif+qnorm(0.975)*se2,cex=0.5,col=rgb(1,0,0,0.2))
points(d,cdif-qnorm(0.975)*se2,cex=0.5,col=rgb(0,0,1,0.2))
#numerical output for the confidence bands is given by
#cdif+qnorm(0.975)*se2
#cdif-qnorm(0.975)*se2
#confidence intervals when seWithMea...
2008 Jun 12
1
About Mcneil Hanley test for a portion of AUC!
...e whole AUC's .
> seROC<-function(AUC,na,nn){
> a<-AUC
> q1<-a/(2-a)
> q2<-(2*a^2)/(1+a)
> se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
> se
> }
>
> cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
> se1<-seROC(AUC1,na1,nn1)
> se2<-seROC(AUC2,na2,nn2)
>
> sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
> zad<-(AUC1-AUC2)/sed
> p<-dnorm(zad)
> a<-list(zad,p)
> a
Could somebody kindly suggest me how to calculate the value of "r" or
some ways to calculate the statistical significance measure for t...
2009 Oct 16
2
RODBC sqlSave does not append the records to a DB2 table
...d the current version RODBC. Unfortunately, it did
not bring any joy. I asked the database adminstrator try it, and she had a
similar experience. No error message is returned, but the record is not
inserted to the table.
For testing purposes, I have a very simple one-row, three-column
data.frame (se2) I want to insert into a DB2 table.
> sqlSave(channel, se2, tablename = "STORAGE.TEST_APPEND2", append = TRUE,
+ rownames = FALSE, colnames = FALSE,
+ verbose = TRUE,
+ safer = TRUE, addPK = FALSE,
+ fast = FALSE, test = FALSE, nastring = NULL)
Query: INSERT...
2011 Jul 11
1
Finding Confidence Intervals
...r
making the right conclusions. Furthermore, there has to be a more efficient
way to perform this task in R.
For a given conversion rate (p) and number of trials (n):
p1 = 0.1
n1 = 1000
se1 = sqrt( p1 * (1-p1) / n1 )
se1
se1 * 1.96
(p1 + 1.96*se1) * 100
(p1 - 1.96*se1) * 100
p2 = 0.11
n2 = 1300
se2 = sqrt( p2 * (1-p2) / n2 )
se2
se2 * 1.96
(p2 + 1.96*se2) * 100
(p2 - 1.96*se2) * 100
(8.1, 11.8) # headline 1
(9.2, 12.7) # headline 2
# these confidence intervals for the two headlines overlap.
# therefore, the variation (headline 2) isn't more effective
# than the control headline
Thanks a...
2006 Mar 15
1
How to compare areas under ROC curves calculated with ROCR package
...archives :
From: Bernardo Rangel Tura
Date: Thu 16 Dec 2004 - 07:30:37 EST
seROC<-function(AUC,na,nn){
a<-AUC
q1<-a/(2-a)
q2<-(2*a^2)/(1+a)
se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
se
}
cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
se1<-seROC(AUC1,na1,nn1)
se2<-seROC(AUC2,na2,nn2)
sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
zad<-(AUC1-AUC2)/sed
p<-dnorm(zad)
a<-list(zad,p)
a
}
The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the
second function (cROC) compare ROC curves."
What do y...
2006 Mar 20
1
How to compare areas under ROC curves calculated with ROC R package
...archives :
From: Bernardo Rangel Tura
Date: Thu 16 Dec 2004 - 07:30:37 EST
seROC<-function(AUC,na,nn){
a<-AUC
q1<-a/(2-a)
q2<-(2*a^2)/(1+a)
se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
se
}
cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
se1<-seROC(AUC1,na1,nn1)
se2<-seROC(AUC2,na2,nn2)
sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
zad<-(AUC1-AUC2)/sed
p<-dnorm(zad)
a<-list(zad,p)
a
}
The author of this script says: "The first function (seROC) calculate the
standard error of ROC curve, the
second function (cROC) compare ROC curves."
What do y...
2007 Apr 17
3
Extracting approximate Wald test (Chisq) from coxph(..frailty)
Dear List,
How do I extract the approximate Wald test for the
frailty (in the following example 17.89 value)?
What about the P-values, other Chisq, DF, se(coef) and
se2? How can they be extracted?
######################################################>
kfitm1
Call:
coxph(formula = Surv(time, status) ~ age + sex +
disease + frailty(id,
dist = "gauss"), data = kidney)
coef se(coef)
age 0.00489...
2010 Nov 29
1
Evaluation of survival analysis
...survival analysis, please?
For example, the results from Cox regression and Parametric survival
analysis are shown below. Which method is prefered and how to see that / how
to compare the methods?
1. coxph(formula = y ~ pspline(x1, df = 2))
coef se(coef) se2 Chisq DF
p
pspline(x1, df = 2), line 0.0522 0.00867 0.00866 36.23 1.00 1.8e-09
pspline(x1, df = 2), nonl 3.27 1.04
7.5e-02
Iterations: 4 outer, 13 Newton-Raphson
Theta= 0.91
Degrees of freedom for terms= 2
Likelihood ratio test=34.6 on 2.04 df...
2013 Jan 23
1
mixed effects meta-regression: nlme vs. metafor
...nt I use a linear model, i.e., twice the followup time will
give you twice the effect, etc...
I get /almost/ what I want using "nlme" via this command:
lme01 <- lme(effect ~ treatment + treatment*time - time - 1,
random = ~ 1|study,
weights = varFixed(~se2),
data = dat)
"effect" is the real-valued measurement, "treatment" is a factor, and
"time" is the followup time in months. "se2" is the squared standard error.
Problem is: using the "varFixed()" option, "lme()" will fit an...
2018 Jan 28
0
Polly Dependency Analysis in MyPass
...&SE = getAnalysis<ScalarEvolutionWrapperPass>().getSE();
auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree();
Result2.reset(new ScopDetection(F, DT, SE, LI, RI, AA));
auto &SD2 = getAnalysis<polly::ScopDetectionWrapperPass>().getSD();
auto &SE2 = getAnalysis<ScalarEvolutionWrapperPass>().getSE();
auto &LI2 = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
auto &AA2 = getAnalysis<AAResultsWrapperPass>().getAAResults();
auto const &DL2 = F.getParent()->getDataLayout();
auto &DT2 = getAnalysis&l...
2006 Feb 16
2
how to retrieve robust se in coxph
Hi,
I am using coxph in simulations and I want to store the "robust se" (or
"se2" in frailty models) for each replicate. Is there a function to retrieve
it, like vcov() for the variance estimate? Thanks!
Lei Liu
Assistant Professor
Division of Biostatistics and Epidemiology
Dept. of Public Health Sciences
School of Medicine
University of Virginia
3181 Hospital West Co...
2009 Oct 28
1
need help explain the routine input parameters for seROC and cROC found in the R archive
...004 - 07:30:37 EST
>
> seROC<-function(AUC,na,nn){
> a<-AUC
> q1<-a/(2-a)
> q2<-(2*a^2)/(1+a)
> se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
> se
> }
>
> cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
> se1<-seROC(AUC1,na1,nn1)
> se2<-seROC(AUC2,na2,nn2)
>
> sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
> zad<-(AUC1-AUC2)/sed
> p<-dnorm(zad)
> a<-list(zad,p)
> a
> }
>
--
Waverley @ Palo Alto
2009 Jul 29
2
cannot allocate a vector with 1920165909 length
Dear Rusers,
The error for the following was that it cannot allocate the vector of
length 1920165909.
a <- expand.grid(se1=0:100/100, sp1=0:100/100, se2=0:100/100, sp2=0:100/100,
DR=0:100/100)
How to solve it? Maybe setwd(dir) can, i am not very sure about it.
Any ideas about it?
[[alternative HTML version deleted]]
2018 Jan 28
4
Polly Dependency Analysis in MyPass
Hello,
I need to analyze dependencies in my llvm ir by using polly. i created a
new pass called mypass there i added polly dependency analysis pass but
when i execute this pass in gdb i get no data.
Why is that so?
My code is follows;
namespace {
struct mypass : public FunctionPass {
static char ID;
mypass() : FunctionPass(ID) {
}
virtual bool runOnFunction(Function &F)
{
2004 Dec 15
3
(no subject)
Dear R-helper,
I would like to compare the AUC of two logistic regression models (same
population). Is it possible with R ?
Thank you
Roman Rouzier
[[alternative HTML version deleted]]
2018 Jan 28
1
Polly Dependency Analysis in MyPass
...perPass>().getSE();
> auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree();
> Result2.reset(new ScopDetection(F, DT, SE, LI, RI, AA));
>
>
>
> auto &SD2 = getAnalysis<polly::ScopDetectionWrapperPass>().getSD();
>
>
>
> auto &SE2 = getAnalysis<ScalarEvolutionWrapperPass>().getSE();
> auto &LI2 = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
> auto &AA2 = getAnalysis<AAResultsWrapperPass>().getAAResults();
> auto const &DL2 = F.getParent()->getDataLayout();
> auto &...
2011 Apr 08
1
Variance of random effects: survreg()
...(x, mean = mu, scale= 0.5, distribution = "weibull"),
Status = rep(1, 100),
Unit = gl(10,10)
)
mod1 <- survreg(Surv(Time, Status) ~ 1 + frailty.gaussian(Unit), data = test1)
> mod1
...
coef se(coef) se2 Chisq DF p
(Intercept) 0.987 0.582 0.0457 2.87 1.00 9.0e-02
frailty.gaussian(Unit) 85.26 8.95 1.4e-14
Scale= 0.434
Iterations: 5 outer, 17 Newton-Raphson
Variance of random effect= 3.37
...
It is not clear from the returned list how to get t...
2017 Nov 02
0
Cox Regression : Spline Coefficient Interpretation?
...gt;> data=FNMA)coxph(formula = Surv(START, STOP, ZEROBAL == 1) ~
>> pspline(OPTION), data = FNMA)> > Option.test2> Call:> coxph(formula =
>> Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION),> data = FNMA)>
>> coef se(coef) se2 Chisq DF
>> p> pspline(OPTION), linear -0.1334 0.0131 0.0131 104.4325
>> 1.00 <0.0000000000000002> pspline(OPTION), nonlin
>> 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19
>> Newton-Raphson> Theta= 0.991> Degre...
2017 Nov 01
3
Cox Regression : Spline Coefficient Interpretation?
...e(OPTION),
> data=FNMA)coxph(formula = Surv(START, STOP, ZEROBAL == 1) ~
> pspline(OPTION), data = FNMA)> > Option.test2> Call:> coxph(formula =
> Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION), > data = FNMA)>
> coef se(coef) se2 Chisq DF
> p> pspline(OPTION), linear -0.1334 0.0131 0.0131 104.4325
> 1.00 <0.0000000000000002> pspline(OPTION), nonlin
> 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19
> Newton-Raphson> Theta= 0.991 > Degrees of freedom...