similar to: how do i vectorize relational queries in R

I have created a list of tables with the same columns but different number of row. Example (actual list has ~200 elements): > temp1<- data.frame(ID=c("Herb","Shrub"),stat=c(4,5),pvalue=c(.03,.04)) > temp2<- data.frame(ID=c("Herb","Shrub", > "Tree"),stat=c(12,15,13),pvalue=c(.2,0.4,.3)) > L<-list(a=temp1,b=temp2) > L $a

I have a function (see below). This function has one object, ID. If I run the loops by themselves using a character value (ie,"VFFF1-7") instead of the function object, then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop

Dear WizaRds, having met some of you in person in Vienna, I think even more fondly of this community and hope to continue on this route. It was great talking with you and learning from you. Thank you. I am trying to work through an artificial example in post stratification. This is my dataset: library(survey) age <- data.frame(id=1:8, stratum=rep(

Dear WizaRds, Working through sampling theory, I tried to comprehend the concept of stratification and apply it with Survey to a small example. My question is more of theoretic nature, so I apologize if this does not fully fit this board's intention, but I have come to a complete stop in my efforts and need an expert to help me along. Please help: age<-matrix(c(rep(1,5), rep(2,3),

Dear list, I got some surprising results when using the svytotal routine from the survey package with data containing missing values. Some example code demonstrating the behaviour is included below. I have a stratified sampling design where I want to estimate the total income. In some strata some of the incomes are missing. I want to ignore these missing incomes. I would have expected that

Dear R Users, I have searched through the archives but I am still struggling to find a way to process the below dataset. I have a dataset that has stratum and plot identifier. Within each plot there is variable (Top) stating the number of measurments that should be used to to calculate the mean to the largest "top" elements within one of the vectors (X). I would like to process

Dear all, We are analysing some survey data and we are not sure if we are using the correct syntax for our design. The population of interest is a set of 4416 polygons with different sizes ranging from 0.003 to 45.6 ha, 7460 ha in total. Each polygon has a binary attribute (presence/absence) and we want to estimate the probability of presence in the population. We used sampling with replacement

Hi, I am playing with clogit(case~spontaneous+induced+strata(stratum),data=infert) from clogit help file. This line works. 1. But, why strata(stratum) doesn't have a coefficient like spontaneous and induced? 2. When I remove strata(stratum) from the command, this function seems to keep running forever. Why? 3. I think the equation for clogit looks like P=1/(1+

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one without stratifying, however, I will need to stratify to meet PH assumptions. This is where I go wrong, but I'm not sure where. Non-Stratified Nomogram:

i've dovecot --version 1.2.5 hg log | grep changeset | head -n 1 changeset: 9407:a3e16df805e3 in my logs, i'm seeing ... Oct 05 16:51:40 dovecot: Error: Time just moved backwards by 1 seconds. I'll sleep now until we're back in present. http://wiki.dovecot.org/TimeMovedBackwards Oct 05 17:07:22 dovecot: Error: Time just moved backwards by 1 seconds. I'll sleep now

Hi all, I wonder whether, for an anova with multiple error strata, it is possible to produce the same diagnostoc plots than with a single-stratum anova. I can extract the residuals for each stratum with e.g. > resid(split1.aov[["block:plot"]]) > resid(split1.aov[["Within"]]) and then produce qqnorm plots etc manually, but is it possible to get all the plots

Why do I see this error? > library(stats) > require(stats) [1] TRUE > > tHSD <- TukeyHSD(aov) Error in TukeyHSD(aov) : no applicable method for "TukeyHSD" In case it helps: > aov Call: aov(formula = roi ~ (Cue * Hemisphere) + Error(Subject/(Cue * Hemisphere)), data = roiDataframe) Grand Mean: 8.195069 Stratum 1: Subject Terms: Residuals Sum

Hy Guys, My samba version: 4.0.13 ntp version: 4.2.6p3 Ubuntu 12.04.3 LTS I have a weird problem, I sat up the time service via https://wiki.samba.org/index.php/Configure_NTP On the servers I have no firewall. This port is open when i check with nmap, ntp runs. Looks like all of my Windows 7 clients works fine but w32tm /resync says Permission denied 0x8007005, so not that good :) Windows

Hi, I’m new to R (just installed today) and I’m trying to figure out how to do stratified randomisation using it. My google search expedition has lead me to believe that blockrand package will most probably be the answer to it. I’ve played around with blockrand for awhile and tried the sample code: library(blockrand) ##stratified by sex male <- blockrand(n=100,

Dear List, Im new to R - making a transition from SAS. I have a space delimited file with the following structure. Each line in the datafile is identified by the first letter. A = Inventory (Inventory) X = Stratum (Stratum_no Total Ye=year established) P = Plot (Plot_no age slope= species) T = Tree (tree_no frequency) L = Leader (leader diameter height) F = Feature (start_height finish_height

Dear R users: I am not entirely convinced that clogit gives me the correct result when I use pspline() and maybe you could help correct me here. When I add a constant to my covariate I expect only the intercept to change, but not the coefficients. This is true (in clogit) when I assume a linear in the logit model, but the same does not happen when I use pspline(). If I did something similar

I have 30 identical Lenovo desktop systems running CentOS 5.1. On one of those systems the clock is running slow (5+ minutes from yesterday to this morning and another minute since this morning) despite the fact that NTP is running on all of them and they all have the exact same /etc/ntp.conf file (I compared the MD5 sums of that file on all the systems). Here is the output of

Greetings. I'm getting started learning R, and I'm trying to reproduce some models I've done previously in SAS. I'm trying to fit simple Poisson regressions, and I keep getting impossible results: the models predict negative numbers of cases for many observations. The code for the models are: Female.model <- glm(Observed ~ Black + Other, family = poisson(link=log),

Hello, I am analyzing the results of a survey of the student body on the use of certain technologies. The student body was divided in strata according to two criteria, college and user class. The resulting 24 strata were sampled. Subjects filled out a survey with a number of questions, most of them of the yes-no variety. I created a data.frame with the results for the survey. One row for

Dear R-help, I'm facing a problem with defining a repeated measures anova with weighted data. Here's the code to reproduce the problem: # generate some data seed=11 rtrep <- data.frame(rt=rnorm(100),ti=rep(1:5,20),subj=gl (20,5,100),we=runif(100)) # model with within factor for subjects/repeated measurements, no problem aov(rt~ti + Error(subj/ti),data=rtrep) #model with weights