similar to: Is there any design based two proportions z test?

Displaying 20 results from an estimated 1000 matches similar to: "Is there any design based two proportions z test?"

2024 Jan 17
1
Is there any design based two proportions z test?
Dear Md Kamruzzaman, To answer your second question first, you could just use the svychisq() function. The difference-of-proportion test is equivalent to a chisquare test for the 2-by-2 table. You don't say how you computed the confidence intervals for the two separate proportions, but if you have their standard errors (and if not, you should be able to infer them from the confidence
2024 Jan 17
1
Is there any design based two proportions z test?
Hello Everyone, I was analysing big survey data using survey packages on RStudio. Survey package allows survey data analysis with the design effect.The survey package included functions for all other statistical analysis except two-proportion z tests. I was trying to calculate the difference in prevalence of Diabetes and Prediabetes between the year 2011 and 2017 (with 95%CI). I was able to
2023 Nov 03
1
[EXTERNAL] RE: I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Yes, that will halve the number of multiplications. If you?re looking for such optimisations then you can also consider ifelse(G=='male', 65L, 58L). That will definitely use less time & memory if WC is integer, but the trade-offs are more complicated if WC is floating point. Regards, Jorgen Harmse. From: avi.e.gross at gmail.com <avi.e.gross at gmail.com> Date: Friday,
2023 Nov 03
2
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Well, something like: LAP <- ifelse(gender =='male', (WC-65)*TG, (WC-58)*TG) The exact code depends on whether your variables are in a data frame or list or whatever, which you failed to specify. If so, ?with may be useful. Cheers, Bert On Fri, Nov 3, 2023 at 3:43?AM Md. Kamruzzaman <mkzaman.m at gmail.com> wrote: > Hello Everyone, > I have three variables: Waist
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) That will do both calculations and merge the two vectors appropriately. It will use extra memory, but it should be much faster than a 'for' loop. Regards, Jorgen Harmse. ------------------------------ Message: 8 Date: Fri, 3 Nov 2023 11:10:49 +1030 From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>
2009 Feb 26
1
error message and convergence issues in fitting glmer in package lme4
I'm resending this message because I did not include a subject line in my first posting. Apologies for the inconvenience! Tanja > Hello, > > I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when
2023 Nov 03
1
I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
Hello Everyone, I have three variables: Waist circumference (WC), serum triglyceride (TG) level and gender. Waist circumference and serum triglyceride is numeric and gender (male and female) is categorical. From these three variables, I want to calculate the "Lipid Accumulation Product (LAP) Index". The equation to calculate LAP is different for male and females. I am giving both
2007 Jun 26
2
Aggregation of data frame with calculations of proportions
Dear all, I have been stuck on this problem, am rather struggling and would appreciate some advice if anyone can help. I apologise if this is a bit long-winded, but I've tried to limit it to the bare essentials, but don't know how to make it more generic! I have some slightly odd real world data that I'm looking at representing number of positive diagnoses for different diseases,
2009 Feb 26
1
(no subject)
Hello, I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when expanding the number of covariates I usually encounter the following error message. gm8 <-
2008 Jan 02
6
problem when editing record in polymorphic relation
I have the following three models created applying the polymorphic concept ========================================================================== class SoftwareCi < ActiveRecord::Base has_one :ci, :as => :content end class HardwareCi < ActiveRecord::Base has_one :ci, :as => :content end class Ci < ActiveRecord::Base belongs_to :content, :polymorphic => true end The
2009 Nov 27
2
layers in xYplot of Hmisc
In the "filled bands" part of xYplot of the Hmisc package, is there a way to have multiple bands with multiple lines? or does it just allow one for now? So I had an example bit ago had a made up line and CI, now if I wanted to make a second line with a CI filled in can I put them on the same plot? x<-seq(1,10,1) y<-seq(1,10,1) ci<-y*.10 ciupper<-y+ci
2002 Jun 06
2
R correlations.
Hi, anybody have any ideas on this ? I have two sequences of proportions. Due to conventions in my field, I need to produce a linear correlation between the two. Each sequence of proportions are based upon differing numbers of observations (although within a sequence the number of observations may not fluctuate too much) so it may be necessary/advisable to variance stabilize. Is their a best
2011 Jun 16
2
Bayesian Credible Intervals for a Proportion
I am trying to calculate Bayesian Credible Intervals for a proportion (disease prevalence values to be more specific) and am having trouble using R to do this. I am working with ncredint() function but have not had success with it. Please help! Example: Positive samples = 3 Total sampled = 10 Prevalence = 0.3 pvec <- seq(1,10,by=1) npost = dbinom(pvec,10,prob=0.3, log=FALSE) ncredint(pvec,
2011 Jul 26
4
[LLVMdev] How to get the return address on the stack on LLVM
Hi all, I want to implement the Xor random canary, so I have to get the return address in the prologue and epilogue of the function. In the prologue of the function, before I insert into the canary on the stack, I can get the return address by: ConstantInt* ci = llvm::ConstantInt::get(Type::getInt32Ty(RI->getContext()), 0); Value* Args1[] = {ci}; CallInst* callInst =
2006 Feb 01
1
several plots in one
Can anyone tell me how I can supply more than one graph to plotCI (gplots) at once? Below is what I tried, also with rbind instead of cbind. What is the way to do this (in general, I think)? Problem is that lines of 1-st and 2-nd series are mixed, while they have nothing to do with each other. I also tried calling plotCI with argument add=TRUE, which didn't seem to work (that is actually
2011 Jul 26
0
[LLVMdev] How to get the return address on the stack on LLVM
On 7/26/11 5:37 PM, Xueying ZHANG wrote: > Hi John, > > Thanks for your reply! I'm CC'ing this to the list in case anyone knows why you're seeing this behavior. > > Now, I know the different between llvm.returnaddress(0) and > llvm.returnaddress(1). I modify the StackPortector.cpp and I just want > to get value of the return address stored on the stack. >
2009 Jul 10
1
prevalence in logistic regression lrm()
Hi, I am wondering if there is a way to specify the prevalence of events in logistic regression using lrm() from Design package? Linear Discriminant Analysis using lda() from MASS library has an argument "prior=" that we can use to specify the prevalent of events when the actual dataset being analyzed does not have a representative prevalence. How can we incorporate this information in
2010 Sep 03
2
Interactions in GAM
Hello R users, I am working with the GAM to inspect the effect of some factors (year, area) and continuous variables (length, depth, latitude and longitude) on the intensity and prevalence of the common parasite Anisakis. I would like introduce interaction in my models, both "continuous variables-continuous variables" and "continuous variables-factor". I have read some
2012 Oct 03
2
Legend Truncated Using filled.contour
Hey everyone, I'm working on a contour plot depicting asymptomatic prevalence at varying durations of infectiousness and force of infection. I've been able to work everything out except for this one - my legend title keeps getting cut off. Here's what I have: filled.contour(x=seq(2,30,length.out=nrow(asym_matrix)), y=seq(1,2,length.out=ncol(asym_matrix)), asym_matrix, color =