search for: unadjust

Hello, I am learning to use the metafor package to conduct meta-regression analyses for a systematic review on multidisciplinary care interventions in chronic kidney disease. For the forest plots, I can't figure out how to plot unadjusted and adjusted models on the same plot. From top to bottom, I would like to be able have the unadjusted plot, the multivariate adjusted plot, then each univariate adjusted plot. Below each plot I would like to also include a polygon with the respective summary estimate and confidence interval. I...

...; >> Time.now => Mon Jul 17 15:56:54 UTC 2006 >> ''I am in central time and the current time is 12:04 pm'' => "I am in central time and the current time is 12:04 pm" >> drew.tz.adjust(Time.now) => Mon Jul 17 09:57:40 UTC 2006 >> drew.tz.unadjust(Time.now) => Mon Jul 17 21:57:55 UTC 2006 None of the above say 12:04pm,, which was the time when I ran this script. I am in central time and the time_zone for this user is central time as well. What am I doing wrong here? Thanks a lot for your help. Thank You, Ben Johnson E: bjohnson@co...

...ot;2012-09-16"), redemption=100, callSch = callSch) dateparams <- list(settlementDays=3, calendar="us", dayCounter = "ActualActual", period="Quarterly", businessDayConvention = "Unadjusted", terminationDateConvention= "Unadjusted") coupon <- c(0.0465) CallableBond(bondparams, HullWhite, coupon, dateparams) # ...I get the following error: # ---> SET_VECTOR_ELT() can only be applied to a 'list', not a 'symbol' <---...

Hello, Thank you for your help/advice! The issue here is speed/efficiency. I can do what I want, but its really slow. The goal is to have the ability to do calculations on my data and have it adjusted for look-ahead. I see two ways to do this: (I'm open to more ideas. My terminology: Unadjusted = values not adjusted for look-ahead bias; adjusted = values adjusted for look-ahead bias.) 1) I could a) do calculations on unadjusted values then b) adjust the resulting values for look-ahead bias. Here is what I mean: a) I could say the following using time series of val1: [(val1 - val1 4 pe...

...ot;,"--","--","--","--","20090319", "--","--","--","--","--","--","--","--"), nrow=8,ncol=4) dimnames(rd1) = list(z.dates,nms) # this is the unadjusted raw data, that always has the same dimensions, rownames, and colnames as the report dates ua = matrix(c(640.35,636.16,655.91,657.41,682.06,702.90,736.15,667.65, 2625.050,2625.050,2645.000,2302.000,1972.000,1805.000,1547.000,1025.000, NaN, NaN,-98.426,190.304,180.894,183.220,172.520...

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks

...ast download yourself but depending on what you want to do with the data you may get misleading results. For example, if the stock trades at $100 and there is a 2 for 1 split then the next day there will be twice as many shares with each share at $50. If the stock does not move that day then the unadjusted return is -50% whereas the adjusted return is 0%. - if the data _is_ adjusted for splits and dividends you will still have this problem if you just add new data onto the end of the old data you downloaded. For example, if you use the data you downloaded yesterday and then just download today...

Hi, R users, What may be the best function in R to do variable selection in logistic regression? I have the same number of variables as the number of samples, and I want to select the best variablesfor prediction. Is there any function doing forward selection followed by backward elimination in stepwise logistic regression? Thanks, Annie [[alternative HTML version deleted]]

I have a puzzle as to how R is computing Cook's distance in weighted linear regression. In this case cook's distance should be given not as in OLS case by h_ii*r_i^2/(1-hii)^2 divided by k*s^2 (1) (where r is plain unadjusted residual, k is number of parameters in model, etc. ) but rather by w_ii*h_ii*r_i^2/(1-hii)^2 divided by k*s^2, (2) i.e. has the weight in there. Apart from the division this is sum of weighted squares of differences yhat_j - yhat_j[i]. (That is, it is the weighted...

...A above, the definition is a load from the constant-pool. >> This is trivially rematerializable and the spill weight is halved. >> However, in the remainder intervals B, C and D the definition is a >> copy. This is not trivially rematerializable, and the spill weight is >> unadjusted. This means these ranges are considered as expensive as >> non-rematerializable ranges. > > This is the first think to fix. As long as a live-range is rematerializable, we should reflect that properly in the spill weight. > Could you clean up your patch to fix that? Unfortunately...

...IC values are: ? ? ? ?0 ? ? ? ? 1 ? ? ? ? 2 ? ? ? ? 3 ? ? ? ? 4 ? ? ? ? 5 ? ? ? ? 6 ? ? ? NA ? ?-5.838 ? ?-5.837 ? ?-5.846 ? ?-5.845 ? ?-5.847 ? ?-5.847 ? ? ? ?7 ? ? ? ? 8 ? ? ? ? 9 ? ? ? ?10 ? ? ? ?11 ? ? ? ?12 ? -5.846 ? ?-5.847 ? ?-5.849 ? ?-5.847 ? ?-5.845 ? ?-5.843 Is there a way to get "unadjusted" AIC values(i.e. values that match the text)? Additionally, is there a way to force ar() to use BIC and return those values? Thank you. James

...ks expected -------------+--------------------------------- positive | 41 3101 2330.5 negative | 18 1560 2330.5 zero | 49 1225 1225 -------------+--------------------------------- all | 108 5886 5886 unadjusted variance 106438.50 adjustment for ties -282.38 adjustment for zeros -10106.25 ---------- adjusted variance 96049.88 Ho: transfer_2_a = transfer_2_b z = 2.486 Prob > |z| = *0.0129* When running a Wilcoxon signed-rank test > wilcox.test(d...

...https://campus.datacamp.com/courses/importing-and-managing-financial-data-in-r/importing-text-data-and-adjusting-for-corporate-actions?ex=10) (and quantmod documentation) to determine how Alpha Vantage's data is adjusted. Here are my findings: -It seems that Alpha Vantage's OHLC data are unadjusted, and the adjusted close column provided is adjusted for splits, and split-adjusted dividends. -If I use AV's adjusted close column to adjust my OHCL data, my data will be adjusted for splits, and split-adjusted dividends. (So, I can use adjustOHLC(), with argument use.Adjusted = TRUE to adjus...

...-1.54 0.809 -3.120 0.0471 factor(NT)1 2.28 1.310 -0.286 4.8500 factor(SS)1 3.30 0.968 1.400 5.2000 z.IT -2.79 2.230 -7.160 1.5800 z.NH 2.28 1.660 -0.968 5.5300 z.W -1.74 1.490 -4.650 1.1800 Confidence intervals are unadjusted Relative variable importance: factor(SS) factor(MS) z.NH z.IT z.W factor(NT) 0.82 0.33 0.32 0.20 0.07 0.01 Does anyone know what I might be doing wrong? thanks for the help Marcos -- View this message in context: http://r.789695.n4.n...

Hi, I'm trying to teach myself R, and by the way, re-learning statistics using Crawley's "Statistics: an introduction using R". I've reached the regression chapter, and when it deals with non-linear regresion using the nls library I face the following problem: I follow the steps--- >deer<-read.table("c:\\temp\\jaws.txt",header=T) ---data available at

...ple testing procedures mt.plot Plotting results from multiple testing procedures mt.rawp2adjp Adjusted p-values for simple multiple testing procedures mt.reject Identity and number of rejected hypotheses mt.sample.teststat Permutation distribution of test statistics and raw (unadjusted) p-values mt.teststat Computing test statistics for each row of a data frame ------------snip With the information on what the function names are, I can now use the "?" command on each of these functions. But I have a feeling that there is a better way ...Oh FOO REX --...

...slated to 0xf6c59070: sub $0xc,%esp 0xf6c59073: mov 0x14(%esp),%eax 0xf6c59077: mov %eax,0x8(%esp) 0xf6c5907b: mov 0x10(%esp),%ecx 0xf6c5907f: mov %ecx,(%esp) 0xf6c59082: call *%eax 0xf6c59084: add $0xc,%esp 0xf6c59087: ret $0x4 after the "call *%eax" the stack is unadjusted by 4 bytes, hence the stack corruption. 2.1 works fine when the JIT produces code with the same llvm assembly code. What can be causing this? A suspicious is in the absence of `sret' on call void %4([4 x i8]* %0) but, on the call site, the function has the sret attribute: assert( f-&gt...

...ice web_service_api XyzApi .... service specific methods go here... end class WebService < ActionWebService::Base def find_newer_than(created_at) real_class.find(:all, :conditions => [''created_at >= ?'', TimeZone[''London''].unadjust(created_at)]) end ... def real_class Class.const_get(self.class.to_s.gsub(/Service$/, '''')) end ... end ---------------------------------------------------------------------------------- I''d like to do the same for the API''s, but can''t quit...

Hello everyone, Like a lot of people, I have been looking for functions in R doing ANOVA (ok) and performing multicomparisons (like Student-Newman-Keuls, etc.). As I have been a little bit disappointed, I have bee looking through the net for such "open source" softwares. I found one in: http://www.statpages.org/miller/openstat/OS4.html I have begun to use it, and it seems good and

Dear R gurus, I have the following model: appcov.aov <- aov(yield ~ prevyield + trt + block) where prevyield is a continuous numeric covariate and trt and block are factors (yes, I did factor()!) Now, when I do a TukeyHSD, my diff's are all screwed up! For instance: treatment mean for treatmen "E" is 277.25 and for treatment "O" is 279.5, so I figure the diff O-E