similar to: Non-linearity test in R

Hi All, I'm dealing with binary response data for the first time, and I'm confused about what kind of graphics I could explore in order to pick relevant predictors and their relation with response variable. I have 8-10 continuous predictors and 4-5 categorical predictors. Can anyone suggest what kind of graphics I can explore to see how predictors behave w.r.t. response variable... Any

Hi Kim and Others, Can anyone please help me on how can I edit default labels ( "Study 1", "Study 2",...) using forest() - same question as below. Which option I should try? It would be a great help. Thanks in advance, On Sun, Dec 13, 2009 at 7:14 PM, Kim Jung Hwa <kimhwamaillist@gmail.com>wrote: > Hi All, > > I'm using forest() from metafor package to

Hi All, I'm wondering if its possible to write degree in symbol. I would like y-label as "Temperature (degreeF)". where degree should be in symbols. Thanks in advance, #R Code library(lattice) data(barley) barchart(yield ~ variety | site, data = barley, groups = year, layout = c(1,6), ylab = "Temperature (degreeF)", scales = list(x =

Hi All, I'm fitting a Poisson regression. And I want to plot 95% Confidence Interval of Regression Estimates. After coming back to original scale (using following formula): exponential(estimate +/- 1.96*SE), at best I can get the output in the form of estimates, lower_limit, upper_limit values. As far I know forest() in metafor package needs input in the form of estimates and their

Hi All, Can someone help me reshape following data: Var1 Var2 Val A X 1 A Y 2 A Z 3 B X 4 B Y 5 B Z 6 to some kind of matrix/tabular format (preferably as a matrix), may be like Var1 X Y Z A 1 2 3 B 4 5 6 Any help would be greatly appreciated, Kim [[alternative HTML version deleted]]

Hi All, I'm a SAS user but I'm very much interested in learning R. I use ODS system in SAS to make nice frequency tables. Is it possible to export the output of table() [in TABULAR FORM]? So, that I can use those directly for publications? Thank you. # R Code: library(datasets) Orange summary(Orange) # outputing this, not as it is, but in table for. is it possible? ~Kim [[alternative

Hi All, I need a file which I can import to MS Word, I'm trying win.metafile(), but it does not seem to support multiple print commands at once (please see below). Is there an alternative to get plots file which can be used in powerpoint/word? # R code: # this does not work; but same thing works with pdf() library(lattice) win.metafile("test.wmf") p1 <- xyplot(decrease ~

Hi All, I need a small help with following code: I'm trying to convert "dashed lines" to regular ones; and changing default "blue" border color to say "black"... but I'm doing it wrong and its not working. Can anyone help please. Thanks, Code: require(lattice) ex <- data.frame(x=1:10, y=rep(c("A","B"), 5)) bwplot(y~x, data=ex,

Hi All, I'm using glm() in R to perform Poisson regression, I'm wondering if its possible to get equivalent Type 1 / Type 3 Analysis (similar to one in PROC GENMOD). Thanks, Kim [[alternative HTML version deleted]]

Hello! I would like to draw a graph like the following: http://www.optics.rochester.edu/workgroups/cml/opt307/spr04/pavel/plot_small.jpg Aim is to plot confidence intervals of treatments for X(=response1) and Y(=response2) axis simultaneously to visualize aggreement of confidence interval for two responses. Can anyone please provide me some direction to start with? Thanks! -- Kim.

Anyone from Chicago area interested in this course? Please email XLSolutions so they can schedule it in Chicago. We ran out of travel budget in my company :( Date: Wed, 2 Aug 2006 13:20:23 -0700From: elvis@xlsolutions-corp.comSubject: [S] Course***Dr Frank Harrell's Regression Modeling Strategies in R/Splus course *** September 2006 near you (San Francisco, Washington DC, Atlanta)To:

Hello, I want to arrage the label according to my preference eg.. (va, vp, a, b, c) but don't know how to supress default ordering. Any suggestions? Please try the code below: n <- c("va", "vp", "a", "b", "c") p <- c(2, 2,1, 3,5) pm<- c(3,4,2,5,4) pn <- c(1,1,1,2,3) x<-data.frame(cbind(n,p,pm,pn)) library(ggplot2) qplot(x=n,

Hi, I have a question about how I should report the results for a linear mixed effects model where the model includes as predictors three factors (facA, facB and facC), one of which (facA) interacts with the other two. facA and facB have two levels and facC has 3 levels. There are also several other continuous predictors (e.g. varA, varB, varC). My mixed model is specified with the following

Hi, I need further help with my GAMs. Most models I test are very obviously non-linear. Yet, to be on the safe side, I report the significance of the smooth (default output of mgcv's summary.gam) and confirm it deviates significantly from linearity. I do the latter by fitting a second model where the same predictor is entered without the s(), and then use anova.gam to compare the

I'm fitting a lme growth curve model with two predictors and their interaction as predictors. The multilevel model is nested so that level 1 is time within the individual, and level 2 is the individual. I would like to plot the mean group-level trajectories at plus and minus 1 SD from the mean of the main effects composing the interaction term. Thus, the plot should have 4 lines (mean

Please forgive me if you already received this. I had an e-mail sending glitch this morning. http://cran.r-project.org/src/contrib/checkSummary.html reported an error in Design.trans.Rd * checking Rd files ... ERROR Rd files with syntax errors: /var/mnt/hda3/R.check/r-devel/PKGS/Design/man/Design.trans.Rd: unterminated section 'alias' The .Rd file is attached. It begins

Hi All, I'm trying to draw boxplots. I'm having a hard time to get "ticks labels" on multiple panels using 'alternating' option. # R Code: # May not be the best example, please just look into 'scales' option library(lattice) data(OrchardSprays) dta <- subset(OrchardSprays, OrchardSprays$rowpos %in% c(1,2,3)) # Original # This works fine, as you can see

Hello all, My question is how do I write a multilevel regression model of individual responses to environmental predictors that accounts for social interactions between individuals. i.e.; 1) Individual response is nested within a group response. 2) The same environmental predictors apply to both hierarchical levels but, 3) Lower level slope/intercept are also affected by high-level response.

I am fitting a cox PH model w/ 2 predictors, x1 = 0/1 treatment variable and x2=continuous variable. I am using natural splines (ns) to model the effect of x2. I would like to examine the estimated effect of x2 on the hazard. I have tried various approaches (below; let model.fit= fitted model using coxph in survival library): 1. The simplest method appears to be using termplot(model.fit).

I would like to be able to construct hazard rates (or unconditional death prob) for many subjects from a given survfit. This will involve adjusting the ( n.event/n.risk) with (coxph object )$linear.predictors I must be having another silly day as I cannot reproduce the linear predictor: fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian) fit$linear.predictors[1] [1] 2.612756