similar to: Meta-regression of categorical variables

Hi (R 2.13.1, OSX 10.6.8) I am trying to use predict.rma with continuous and categorical variables. The argument newmods in predict.rma seems to handle coviariates, but appears to falter on factors. While I realise that the coefficients for factors provide the answers, the goal is to eventually use predict.rma with ANCOVA type model with an interaction. Here is a self contained example

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

Hi, I am a student using R for my final year project, with the metafor package being particularly helpful. I have been following the steps laid out in the manual 'Conducting Meta-analysis in R with the Metafor package' (Viechtbauer, 2010) and applying it to my own data of infected Anopheles mosquitoes across Africa. In particular, I am attempting to apply a mixed-effect model to my data

Dear useRs, I was searching CRAN for implementation of kurtosis and skewness tests, and found that there is some kind of lack on it. So, I have written three functions: 1. Anscombe-Glynn test for kurtosis 2. Bonett-Seier test based on Geary's kurtosis (which is not widely known, but I was inspired by original paper describing it, found coincidentally in Elsevier database) 3.

Hello, I'm experiencing a kernel panic that appears to be caused by zfs. No errors are making it into /var/log/messages, but here is the error message that appears on my screen after panic (transcribed): panic solaris assert BSWAP_32(sa_hdr_phys->sa_magic) == SA_MAGIC, file: /src/sys/modules/zfs/../../cddl/contrib/opensolaris/uts/common/fs/zfs/sa.c, line 1262 I can reproduce this by

This needs loads more testing before we include it. However it's in good shape for testing and review. Rich. -- Richard Jones, Virtualization Group, Red Hat http://people.redhat.com/~rjones virt-df lists disk usage of guests without needing to install any software inside the virtual machine. Supports Linux and Windows. http://et.redhat.com/~rjones/virt-df/ -------------- next part

configure.ac | 2 libswfdec/swfdec_js_movie.c | 3 - libswfdec/swfdec_root_movie.c | 58 +++++++++++++++++++ libswfdec/swfdec_root_movie.h | 16 ++++- libswfdec/swfdec_script.c | 119 ++++++++++++++++++++++++++++++++-------- libswfdec/swfdec_sprite.c | 6 +- libswfdec/swfdec_sprite.h | 4 - libswfdec/swfdec_sprite_movie.c | 41

libswfdec/swfdec_image.c | 2 libswfdec/swfdec_script.c | 25 +++ libswfdec/swfdec_script.h | 3 test/Makefile.am | 6 test/swfdec_out.c | 10 + test/swfdec_out.h | 3 test/swfedit.c | 2 test/swfedit_list.c | 18 ++ test/swfedit_tag.c | 15 ++ test/swfedit_token.c | 37 +++++ test/swfedit_token.h | 3

libswfdec/js/jsinterp.c | 1 libswfdec/swfdec_bits.c | 108 +++++++++++++ libswfdec/swfdec_bits.h | 4 libswfdec/swfdec_codec_screen.c | 68 +------- libswfdec/swfdec_image.c | 107 ++++++------- libswfdec/swfdec_script.c | 40 +++++ test/Makefile.am | 11 + test/swfdec_out.c | 119 +++++++++++++++ test/swfdec_out.h

libswfdec/swfdec_bits.c | 8 +- libswfdec/swfdec_bits.h | 4 - libswfdec/swfdec_js.c | 92 +++++++++++++++++++++++++--------- libswfdec/swfdec_js.h | 5 + libswfdec/swfdec_script.c | 64 +++++++++++++++++++++-- test/swfdec_out.c | 24 ++++++++ test/swfdec_out.h | 5 + test/swfedit_tag.c | 64 +++++++++++++++++++++++ test/swfedit_token.c |

Makefile.am | 3 configure.ac | 2 doc/swfdec.types | 8 test/Makefile.am | 45 -- test/crashfinder.c | 157 ------- test/dump.c | 448 -------------------- test/swfdec-extract.c | 301 ------------- test/swfdec_out.c | 383

libswfdec/Makefile.am | 2 libswfdec/swfdec_as_context.c | 30 libswfdec/swfdec_as_frame.c | 4 libswfdec/swfdec_as_interpret.c | 2472 +++++++++++++++++++++++++++++++++++ libswfdec/swfdec_as_interpret.h | 45 libswfdec/swfdec_as_object.c | 5 libswfdec/swfdec_as_types.c | 43 libswfdec/swfdec_as_types.h | 5 libswfdec/swfdec_script.c |

libswfdec/js/jsinterp.c | 3 libswfdec/js/jsinterp.h | 1 libswfdec/swfdec_js.c | 51 +++++++++ libswfdec/swfdec_js.h | 8 + libswfdec/swfdec_js_global.c | 30 +++++ libswfdec/swfdec_js_movie.c | 181 +++++++++++++++++++++++++---------- libswfdec/swfdec_movie.c | 22 ---- libswfdec/swfdec_player.c |

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,

configure.ac | 2 doc/swfdec-sections.txt | 5 - libswfdec-gtk/swfdec_playback_alsa.c | 8 +- libswfdec/Makefile.am | 1 libswfdec/jpeg/jpeg.c | 45 ++++++++-------- libswfdec/jpeg/jpeg.h | 2 libswfdec/swfdec_amf.c | 6 +- libswfdec/swfdec_as_array.c

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

Hello, I am performing a meta-analysis using the metafor package. My data are proportions and I used the Freeman Tukey double arcine (FT) transformation to fit the random effects model. Now I want to create a forest plot with my estimates backtransformed to the original scale of proportions. Can this be done? Regards, Patricia

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, I can't get my head around this - can someone give me a pointer: I have a vector of values ('orig') representing areas and I want to calculate the amount contributed by each original vector values in a new vector ('new'). I find this hard to explain so here is a graphical explanation: # CODE START orig <- 10:1 #10 values with varying area new <-

I have a Centos 5.7 machine with Intel I10 video (built-in, I guess -- this is one of those all-in-one mini terminal things) that I'm trying to put a new 1920x1080 monitor onto, without conspicuous success. Prior to this it's been using a smaller monitor with no issues. Try as I might I can't get the new monitor to run at its 1920x1080 resolution. I just realized that I forgot to