search for: assessing

Dear Sir, dear Madam, I am currently working with the European Commission on a pilot assessment of Video Codecs in eGovernment, more precisely for live video streaming of parliamentary sessions. The results of the analysis will be published for public consultation on IDABC <http://ec.europa.eu/idabc/en/home> website. The following video codecs are on the list: H.264/AVC, VC-1,

Hello R help, I have a question similar to what is posted by someone before. my problem is that Instead of last assessment, I want to choose last two. I have a data set with several time assessments for each participant. I want to select the last assessment for each participant. My dataset looks like this: ID week outcome 1 2 14 1 4 28 1 6 42 4 2 14 4 6 46 4 9 64 4 9

Hi, using polynomial contrasts for the ordered factors in an experiment leads to much nicer covariance structure than using treatment contrasts. It is easy to assess the mean effect for each of the experimental groups. However, standard errors are provided only for the components of the orthogonal contrasts. I wonder how to assess the standard errors not of the components, but of the respective

Looking to change a yml file (yaml is a database type file) *** from ?--- !ruby/object:Right attributes: name: Personnel Admin action: index id: "1" controller: assessments --- !ruby/object:Right attributes: name: Personnel Admin action: find id: "2" controller: assessments *** to ?--- !ruby/object:Right attributes_1: name: Personnel Admin action:

Hi, As part of an R code assingment I have been asked to find a quantitative procedure for assessing whether or not the data are normal? I have previously used the graphical procedure using the qqnorm command. Any help/tips would be greatly appreciated as to how I should start going about this! Henry _________________________________________________________________ [[alternat...

Dear R users, Recent changes to the MuMIn package now means that the model averaging command (model.avg) no longer returns confidence intervals, but instead returns zvalues and corresponding pvalues for fixed effects included in models. Previously I have used this package for model selection/averaging following Greuber et al (2011) where it suggests that one should use confidence intervals from

I am trying to trouble shoot one of my ISP's network and compare to my other ISPs offering. Although network 1 is reasonably fast and has low enough latency, voice quality is not good and the reason for this is not readily apparent using standard network tools. What tools can be used to assess the quality of the network in terms of it's suitability for voice? I am using ping, mtr,

Dear R-Helpers Has anyone written a script for the dose proportionality assessement using the power model and the confidence interval criteria as described in - Gough at al. Assessment of dose proportionality: report from the statisticians in the pharmaceutical industry in Drug Information Journal,1995, 29:1039-1048 and/or - Smith et al. Confidence interval criteria for assessment of dose

I am going to be developing a Risk Assessment system for a secure environment whose database will double as an asset management system. Or at least the Risk Assessment stuff will be an outcropping of the asset management system. Has anyone had any experience with this or a similar project? This is my first attempt at a Rails project after spending a few weeks reading books and getting a general

...poor fit for the data from week two. And the sample size is small enough that I would not have confidence in the parameters estimated from a portion of a samlpe to fit against the remainder of the sample. Thanks Ted -- View this message in context: http://www.nabble.com/Statistical-question-re-assessing-fit-of-distribution-functions.-tp19611539p19611539.html Sent from the R help mailing list archive at Nabble.com.

Dear list, I have been struggling with this for some time now, and for the last hour I have been struggling to make a working example for the list. I hope someone out there have some experience with plotting longitudinal data that they will share. My data is some patient data with three different time stamps. First the patients are identified at different times (first time stamp). Second, they

Hello everyone,  There's something really important about climate change and how many institutions around the globe are looking for softwares solutions in order to achieve they (and everyone) needs to improve life conditions in all the planet. Currently, they're many comercial softwares working with this important topic named as: "Life Cycle Assesment", monitoring carbon emition,

I am analyzing a 1-to-2 matched case-control study using clogit in the survival package. I am interested in comparing and assessing fit of non-nested models. I don't want to program all the diagnostics described in Hosmer/Lemeshow (2000). Can someone proficient with clogit and assessing fit for non-nested models point me in the right direction. Many thanks! Tomas Tomas Aragon, MD, DrPH Tel: 510-847-9139 (mobile) URL: htt...

Hi, I'd like to know whether R is capable to assess parameters in a model describing the kinetic of a pollutant adsorption onto activated carbon. A common relation is for instance the Adam-Bohart-Thomas' one: dx/dt = K1 * (qm-x)*C - K2x where {K1,K2} are the unknown paramters and {qm,C} are known parameters Of course I get experimental data sets of measured x as a function of time.

...Secondly, it seems that quasi models cannot be implemented with the function lmer, is there an option? If not, I certainly should go to variable transformation and use a gaussian error distribution, but it is not optimal. Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Assessing-overdispersion-and-using-quasi-model-with-lmer-possible-tp4646626.html Sent from the R help mailing list archive at Nabble.com.

Dear List, I am (again) looking at meta-regression as a way to refine meta-analytic results. What I want to do is to assess the impact of some fixed factors on the results of a meta-analysis. Some of them may be crossed with the main factor of the meta-analysis (e. g. clinical presentation of a disease, defining subgroups in each of the studies under analysis), some of them may be a grouping

...n variant is much smaller that the treatment effect itself); therefore, it is not a big problem to exclude it in the analysis. So I used the rmeta package to assess the treatment effects. The results, as far as I can tell, are not unreasonable. However, I have two problems with this approach : A) Assessing the "variant" effect : how ? ========================================= My main problem is that I can't assess formally the (quite possibly null) effect of the "variant" factor (i. e. checking, at least a posteriori, that the "variant" effect is indeed much smaller...

Hi Folks, Hopefully this question has enough R and not too much stats to be appropriate for this list. Based on,* Hosmer et al. 2013. Logistic regression for matched case-control studies. Applied Logistic Regression *(eqtn. 7.8)*, *I am assessing GOF of conditional (or matched) logistic regression models with the *standardized Pearson residuals*. The authors define ?large? as delta chi-squared values > 4. For a 1:1 study, I can fit a conditional logistic model via an unconditional routine by making the response variable all 1?s, taking...

I want to use lastest version of Shorewall in my fresh debian squeeze instalation, so I follow http://www.shorewall.net/Install.htm#Debian but, modify preferences file was not enough for me, I have to modify/add some other files in /etc/apt/ directory: 1.) include testing repo to source.list 2.) add APT::Default-Release "stable"; to apt.conf and pinning all other packages to stable

...tion time of blocks of samples, which makes the assessment of sampling rates hard, but doesn't affect the actual interpolation. We are talking about two clocks, which are not synchronised, and which may drift in frequency significantly over fairly short periods of time. The issue is accurately assessing the sampling rate difference, to phase locked levels of accuracy, so the resampling is precise. You can find sampling rates like 8000/s and 8100/s, which is a disaster for most echo cancellers. If the clock rate difference is assessed to 0.1Hz accuracy, and the 8100/s sampled signal is resampled to...