similar to: Matrix problem - possibly use of 'outer'

Hi, I'm trying to get to grips with accessing my postgresql tables in R using RODBC. I have Mac OS 10.2.8 (Darwin 6.8) installed and R 1.8.0 installed from source and I have updated RODBC to 1.0-4. On the ODBC manager end, I am using OpenLink software's iODBC Administrator and I've set up a User DSN called "PostGRES" - odbctest suggests that this is functioning: >

Hi, I can't get R-1.7.0 to compile on my Mac. Can someone give me some pointers? The machine is an 800MHz iBook running OS 10.2.6. I have installed the December 2002 Developers Tools and have installed g77, f2c and dlcompat via fink. I've checked the versions of g77 and gcc and they're both based on gcc version 3.1. I've got Apple's X11 (Beta 3). I've added /sw/bin

Hello I've got a question about list indexing. If anyone can help or point in the direction of some documentation, that'd be great. I've checked the Introduction to R and R language definition. Say you have a list of vectors: >

I'm not sure if this is a bug, or if I'm doing something wrong. =20 =46rom the worms dataframe, which is at in a file called worms.txt at =20 http://www.imperial.ac.uk/bio/research/crawley/therbook <http://www.imperial.ac.uk/bio/research/mjcraw/therbook/index.htm>=20 =20 the idea is to extract a subset of the rows, sorted in declining order of worm density, with only the maximum

Hello I'm a population ecologist and use R for all my stats and modelling. Recently I have been using R to numerically solve integral projection models. This involves constructing several large matrices. The current code by Easterling (Size-specific sensitivity: Applying a new structured population model. Ecology, 2000, 81, 694-708) uses nested loops to construct the matrices. To speed up the

Hi, I have a small simple data frame (attached) - to compare diversity of insects encountered in disturbed and unditurbed site. What i have is the count of insects - the total number of times they were encountered over 30 monitoring slots. Can someone please check for me to make sure how the 'community data matrix' for the diversity function needs to be oriented so that i'm

I have been using lme to model data with multiple nested random effects and continuous response variables however I also have data with a binary response variable, binomial errors and multiple levels of nesting of random effects (e.g. site/block/quadrat/year), is there a package available which will do this? Jim Lindsey's package "repeated" appears to be only able to cope with 2

I've been using the nlme library to construct lme models and I'd like to extract an r-sq value for the model - how do I do this? With glm I just used the reported (null deviance-deviance)/(null deviance). Deviance is not reported directly for lme nor can it be extracted using the deviance() function. How do I work out the deviance or can I work out R-sq in some other way? Thanks, Yvonne

Dear metafor users, I am working on a meta-analysis of reliability and the correlation associations. I need some help about conducting categorical moderators variables. Questions 1: How to conduct the weighted ANOVAs assuming a mixed-effects model on the tranformed alpha coefficients/the tranformes correlation coefficients for the categorical moderator variables? Questions 2: How to

I would suggest to post this to the (recently created) R-sig-meta-analysis mailing list. See: https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis Best, Wolfgang >-----Original Message----- >From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Naike Wang >Sent: Monday, June 26, 2017 08:32 >To: R-help at r-project.org >Subject: [R] Classic fail-safe N >

Hi all, I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results. *Below is

Dear R community, I'm using the ,metafor'-package by Wolfgang Viechtbauer (Version: 0.5-5) to calculate random-effects meta-analyses using Correlations and Sample Sizes as the raw data. (By the way: Really a nice piece of work, Wolfgang! Thanks heaps.) I specified the "rma.uni' function so that it looks like this: MAergebnis<-rma.uni(ri=PosOutc, ni=N,

Dear list, I would like to create a time series plot in which the paths of several individuals are stacked above each other, with the x-axis being the total observation period of three years ( 1.1.2004 to 31.12.2007) and the y-axis being some defined range[min,max]. My data consist of Date/Time information and the paths of 45 individual as the distance from the location of release. An example

Hi all, I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results. *Below is

In a Box and Whisker plot, I thought that when there are outliers both abov= e and below the whiskers, then the whiskers should both be the same length = (plus or minus 1.5 times the inter-quartile range). If you look at the plot for SilwoodWeather on p.155 of The R Book you will = see that for November (month =3D 11) the upper whisker is shorter than the = lower, while for other months with

Dear all, I have a question about the lattice package, more specifically about the control of the x-axis length in the different panels. I use the following code to make the stacked barchart: barchart(country ~ climatechangefocalpoint + meteorologyservice + adaptationorvulnerability + cdmcarbonmarkets + energy + aviationmaritimetransport + forestry + pressofficer|period, data=graph5,

Dear users of metafor, I am working on a meta-analysis using the metafor package. I have a excel csv database that I am working with. I am interested in pooling the effect measures for a particular subgroup (European women) in this csv database. I am conducting both sub-group and meta-regression. In subgroup-analyses, I have stratified the database to create a separate csv file just for European

In this real example (below), all four of the replicates in one treatment combination had zero failures, and this produced a very high standard error in the summary.lm. =20 Just adding one failure to one of the replicates produced a well-behaved standard error. =20 I don't know if this is a bug, but it is certainly hard for users to understand. =20 I would value your comments=20 =20 Thanks =20

Hi all, I am not a very proficient R-user yet, so I hope I am not wasting people?s time. I want to run a linear mixed model with 3 random factors (A, B, C) where A and B are partially crossed and C is nested within B. I understand that this is not easily possible using lme but it might be using lmer. I encountered two problems when trying: Firstly, I can enter two random factors in lmer but

Hi, I'm have a list of integer vectors and I want to perform an outer() like operation on the list. As an example, take the following list: mylist <- list(1:5,3:9,8:12) A simple example of the kind of thing I want to do is to find the sum of the shared numbers between each vector to give a result like: result <- array(c(15,12,0,12,42,17,0,17,50), dim=c(3,3)) Two for() loops is the