similar to: Regression function lm() not giving proper results

Hi, R-users, data is a matrix like this AMR BS GE HR MO UK SP500 1974 -0.3505 -0.1154 -0.4246 -0.2107 -0.0758 0.2331 -0.2647 1975 0.7083 0.2472 0.3719 0.2227 0.0213 0.3569 0.3720 1976 0.7329 0.3665 0.2550 0.5815 0.1276 0.0781 0.2384 1977 -0.2034 -0.4271 -0.0490 -0.0938 0.0712 -0.2721 -0.0718 1978 0.1663 -0.0452 -0.0573 0.2751 0.1372 -0.1346

Folks, I have the following dataframe: > x <- structure(list(name = c("EU B", "EU B", "EU B", "EU B", "EU B", "EU B", "AU A", "AU A", "AU A", "AU A", "AU A", "AU A"), date = c("2010-10-11", "2010-10-12", "2010-10-13",

Full_Name: Mike Ulrich Version: 2.9 OS: Mac OSX Submission from: (NULL) (69.169.178.34) The help documentation for loadings() lists more then one parameter. The function call only expects one parameter. The digits, cutoff, and sort parameters are not used in the function. ## S3 method for class 'loadings': print(x, digits = 3, cutoff = 0.1, sort = FALSE, ...) ## S3 method for class

Hello: In the example below (or for a censored data) using survfit.coxph, can anyone point me to a link or a pdf as to how the probabilities appearing in bold under "summary(pred$surv)" are calculated? Do these represent acumulative probability distribution in time (not including censored time)? Thanks very much, parmee *fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)*

I am having problems with comparing individual means in a within-subjects ANOVA. From my understanding, TukeyHSD is not appropriate in this context. So I am trying to compute contrasts, as follows: seven subjects participated in each of 6 conditions (intervals). > subject = factor(rep(c(1:7), each = 6)) > interval = factor(rep(c(1:6), 7)) and here is the dependent variable: > dv

Hi All , Can anybody tell me if there's any way to get the summarized anova values.Now i will explain what i mean , when i say "*summarized*". Below you can see the anova table of recmeanC1 with rest* all* i.e from recmeanC2 to i15(predictors),as shown in table. Df Sum Squares Mean Square F value Significance [Pr(>F)] recmeanC2 1 89.272 89.272

I have dataframe with 17factors variables (for example every factor have 3levels) I have maybe 5000 observation. And i need to do table where is in every raw 1 of possible combination of this factors and the numbur how many time is this combination in my dataset. I wrote one code, but this is very slow and dumb. it looks like this: i<-0 for(i1 in levels(hivdat$pohl)){

Hi LLVM-Devs, I have managed to complete updating our sources from LLVM v4.0 to v5.0, but I am getting selection errors for 'callseq_end'. I am aware that the 'ADJCALLSTACKUP' and 'ADJCALLSTACKDOWN' patterns have changed, and have added an additional argument to the TD descriptions for these. There are interactions with 'ISD::CALL' and 'ISD::RET_FLAG',

Dear friends, In R, the help of "bic.glm" tells the difference between postmean(the posterior mean of each coefficient from model averaging) and condpostmean(the posterior mean of each coefficient conditional on the variable being included in the model), But it's still unclear about the results explanations, and the artile of Rnews in 2005 on BMA still don't give more detail on

Hi, I am doing a hierarchical CFA using the sem package. I have 20 items, and I have 2 factors (F3 and F4), and also F1 and F2 are nested within F3. Here is the code that I have, but it is giving me an error message "Warning message: In eval(expr, envir, enclos) : Negative parameter variances. Model may be underidentified." and a further error "Error in summary.objectiveML(cfa,

> Hello, > > I have a question about a discrepancy between the > reported F statistics using anova() and add1() from > adding an additional term to form nested models. > > I found and old posting related to anova() and > drop1() regarding a glm with a dispersion parameter. > > The posting is very old (May 2000, R 1.1.0). > The old posting is located here. >

Hi Martin, Pseudo CALLSEQ_START was changed in r302527, commit message contains details on the changes. However CALLSEQ_END was not modified. If your made changes to ADJCALLSTACKUP to add additional argument, that may result in error. Thanks, --Serge 2017-09-15 19:09 GMT+07:00 Martin J. O'Riordan via llvm-dev < llvm-dev at lists.llvm.org>: > Hi LLVM-Devs, > > I have managed

Hi all, hope someone can help me out with this. Background Introduction I have a data set consisting of data collected from a questionnaire that I wish to validate. I have chosen to use confirmatory factor analysis to analyse this data set. Instrument The instrument consists of 11 subscales. There is a total of 68 items in the 11 subscales. Each item is scored on an integer scale between 1 to 4.

Hi Im trying something new with my test dovecot. I set my mail_location to to a new location mail_location = maildir:/var/maildir/%u/Maildir But with this new setup i too am authenticating against Mysql. This worked fine till i decided to move the mail. So now i have moved the mail, deleted the account from /etc/passwd,, but now in my mail client, i cant view my test mail. Here is my DB set

How can I get the log odds associated with the levels in strata() within a clogit() model? I'm running R-1.9.0 on a Linux platform. I am using clogit() to run a Rasch model in Item Response Theory in psychometrics. Symbolically, the model is: logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) = \theta_j - \alpha_k, That is, the log odds of answering an test item correctly is

Hi All, Can someone help me?The way to do this may be very easy but i do not know. *Question1:----* factanal() function produces the results in this way:-- *RESULTS:--* *>fact1<- factanal(data_withNA,factors=1,rotation="none") >fact1$"loadings"* Loadings: Factor1 i1 0.784 i2 0.874 i3 0.786 i4 0.839 i5 0.778 i6 0.859 i7 0.850 i8 0.763 i9 0.810 i10 0.575

Dear useRs from the physiology department, Does someone know of an implementation of the SF-36 questionnaire scoring in R? I only found SAS and STATA versions, e.g http://gim.med.ucla.edu/FacultyPages/Hays/util.htm Dieter

I have a dataframe ​df ​ with 3 columns. Details ​of df are ​ as follows > summary(df) Date TestVar type Min. :2002-05-10 00:00:00 Min. :-3.8531 Bottom: 313 1st Qu.:2005-05-09 12:00:00 1st Qu.:-0.7773 Other :2501 Median :2008-05-07 00:00:00 Median : 0.2482 Top : 313 Mean :2008-05-07 00:00:00 Mean : 0.1980 3rd Qu.:2011-05-05

Hello, I've recently come across a situation where I'm trying to read in [genotype data] files that have around 80,000,000 lines, 4 fields, with a high proportion of repeated strings, here's a sample: rsXXXXXXX SAMPLE0001 CG 0.05302 rsXXXXXX SAMPLE0001 CC 0.06817 rsXXXXXXXX SAMPLE0001 CC 0.01369 rsXXXXXXY SAMPLE0001 GG

Hello: When I use SPSS I execute the AGGREGATE DATA comand for the next data: 2112141123212213212213334 3143244113442312121213344 2114141123112214212113344 2112211122212413421213221 3114444123442414343413344 2312231223212222323223322 2143241123212313131213234 2113241113212313222213333 2113141123112214212113344 2114141123412111114413344 2113211122342314222313234 2114141123112414212113344