search for: stepdown

I've been using SAS PROC MULTTEST to perform multiple comparisons on data that are not normally distributed by using the stepdown bootstrap procedures of Westfall and Young (1993). According to the SAS manual, "the bootstrap method creates pseudo-data sets by sampling observations with replacement from each within-stratum pool of observations. An entire data set is thus created, and p-values for all tests are computed o...

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if conf='bands' and labelc was FALSE) * In survfit.cph, fixed bug by which n wasn't always defined * In cph, put survival::: on exact fit call * Q...

Hi, Does R support any of the 3 stepwise or 8 criteria methods for logistic regression and multiple linear regression that SAS supports? If yes, could you give me some simple demostration code. Thanks, steve __________________________________________________ Do You Yahoo!? Make international calls for as low as $.04/minute with Yahoo! Messenger http://phonecard.yahoo.com/

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if conf='bands' and labelc was FALSE) * In survfit.cph, fixed bug by which n wasn't always defined * In cph, put survival::: on exact fit call * Q...

Good afternoon! I need to evaluate the goodness-of-fit (aka calibration) for survival probability estimates from a Cox model. I tried to use 'calibrate' in the Design package but I'm not sure if it should/would produce what I need (ie a chi-sq type statistic with a table of expected vs observed probabilities). Any other functions I should be aware of? Also, has anybody come across

Hello, I have a couple of questions about the ols function in Frank Harrell's rms package. Is there any way to specify variables by their column number in the data frame rather than by the variable name? For example, library(rms) x1 <- rnorm(100, 0, 1) x2 <- rnorm(100, 0, 1) x3 <- rnorm(100, 0, 1) y <- x2 + x3 + rnorm(100, 0, 5) d <- data.frame(x1, x2, x3, y) rm(x1, x2, x3,

Hi, I was wondering whether this query was addressed on how to perform validation through boostrapping. I am currently trying to implement a boostrapping approach to validation but don't know where to start. Help please. Thank you and Regards, Vivienne Ozohili Risk Model Validation Manager Group Risk Independent Control Unit A5, Bank of Ireland Head Office Lower Baggot Street Dublin 2 Tel:

Mark, there is a fdr website link via Yoav Benjamini's homepage which is: http://www.math.tau.ac.il/%7Eroee/index.htm On it you can download an S-Plus function (under the downloads link) which calculates the false discovery rate threshold alpha level using stepup, stepdown, dependence methods etc. Some changes are required to the plotting code when porting it to R. I removed the xaxs="s" arguement on line 80. The fdr function requires a list of p-values as input, a Q-value (*expected* false discovery rate control at level Q) and a required method of fdr co...

You asked the same question on the Bioconductor mailing list back in August. At that time, you suggested yourself a solution for how the adjusted p-values should be interpreted. I answered your query and told you that your interpretation was correct. So I'm not sure what more can be said, except that you should read the article Wright (1992), which is cited in the help entry for p.adjust(),

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the

I am using GLM to calculate logit models based on cross-sectional data. I am now down to the hard work of making the results intelligible to very average readers. Is there any way to calculate a psuedo analoque to the R^2 in standard linear regression for use as a purely descriptive statistic of goodness of fit? Most of the readers of my report will be vaguely familiar and more comfortable with