similar to: Problem in performing goodness of fit test in R.

Hi all, I want to make a contingency table in R. I want to tabulate two variables, one as the independent and second as the dependent variable. The IV has two categories, namely, birth complications, and no birth complications. The frequency of birth complication category is fifty, and the frequency of no birth complication category is 34. The categories and frequencies of DV follows.

Dear list members, I want to save residuals above or less than a certain value to an R object. I have performed a multiple linear regression, and now I want to find out which cases have a residual of above + 2.5 and ? 2.5. Below I provide the R commands I have used. Reg<-lm(a~b+c+d+e+f) # perform multiple regression with a as the dependent variable. Residuals<-residuals(reg) # store

Dear list, I have the following how-to-do it in R, questions. Suppose I have ten independent variables, and one dependent variable. I want to find the Pearson correlation of all the IVs with the DV, but not the correlation between the IVs. What I know so far, about R, that I have to type the cor () function ten times, each time requesting for a correlation between one IV and the DV. I was

Dear list, I am slightly confused about how I can do the following in R. I want to perform robust multiple regression. I?ve used the Boot function in CAR package to find confidence intervals and standard errors. Inadition to these, I want to find the robust estimates for the F test and r-square. Finally, I would like to know the significance levels of bootstrap results. Below I explain

Hi all, I would like to read the results of the commands type in the terminal window in Microsoft Word. As a blind user my options are somewhat limited and are time consuming if I want to see the results of the commands that I have type earlier. for example if my first two commands were x<-c(1,2,3,4,5) mean(x) and I have typed ten more commands after the first two commands it is not easy

Residuals are stored as a numeric vector. The R software comes with a document "Introduction to R" that discusses basic math functions and logical operators that can create logical vectors: abs( stdresiduals ) > 2.5 It also discusses indexing using logical vectors: stdresiduals[ abs( stdresiduals ) > 2.5 ] Note that in most cases it is worth going the extra step of making your

Hi For first question, maybe I am completely wrong but cor(swiss[,-1], swiss[,1]) should give you what you want in one step. Second question Without an example it is hard to say but maybe aggregate is the way forward. > aggregate(iris[,1:4], list(iris$Species), function (x) c(mean=mean(x), sd=sd(x))) Group.1 Sepal.Length.mean Sepal.Length.sd Sepal.Width.mean Sepal.Width.sd 1

Hi all, I am trying to use type message with sink, like this: sink("all.Rout", type="message") 1+3 sink() readLines(con = "all.Rout") So to get the following output: > 1+3 [1] 4 Obviously this doesn't work. I tried some variations (based on the explanations in the help) but am missing something on how to make it work. Any suggestions? (p.s: I need

After reading more, I understand I didn't formulate my last question correctly, so please allow me to rephrase: What I am looking for is a way to save the R console session output. That is, a command that would combine the results of using: ?sink # And ?savehistory My motivation for this is that doing it will allow someone who is a blind user of R to be able to easily export his results to

Dear R-Users, How can I use chisq.test() as a goodness of fit test? Reading man-page I?ve some doubts that kind of test is available with this statement. Am I wrong? X2=sum((O-E)^2)/E) O=empirical frequencies E=expected freq. calculated with the model (such as normal distribution) See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm for X2 used as a goodness of fit test. Any

Dear Faiz, Bootstrapping R^2 using Boot() is straightforward: Simply write a function that returns R^2, possibly in a vector with the regression coefficients, and use it as the f argument to Boot(). That will get you, e.g., bootstrapped confidence intervals for R^2. (Why you want that is another question.) See the example in ?Boot that shows how to bootstrap the estimated error variance (without

Where does the value 2.2e-16 come from in p-values for chisq tests such as those reported below? > Anova(cm.mod2) Analysis of Deviance Table (Type II tests) Response: Freq LR Chisq Df Pr(>Chisq) B 11026.2 1 < 2.2e-16 *** W 7037.5 1 < 2.2e-16 *** Age 886.6 8 < 2.2e-16 *** B:W 3025.2 1 < 2.2e-16 *** B:Age 1130.4 8 < 2.2e-16 *** W:Age 332.9 8 < 2.2e-16 *** --- Signif.

I want to calculate chi square test of goodness of fit to test, Sample coming from Poisson distribution. please copy this script in R & run the script The R script is as follows ########################## start ######################################### No_of_Frouds<- c(4,1,6,9,9,10,2,4,8,2,3,0,1,2,3,1,3,4,5,4,4,4,9,5,4,3,11,8,12,3,10,0,7) N <- length(No_of_Frouds) # Estimation of

In SAS, for a two-way (or 3-way, stratified) table, the CMH option in SAS PROC FREQ gives 3 tests that take ordinality of the factors into account, for both variables, just the column variable or neither. Is there an equivalent in R? The mantelhaen.test in stats gives something quite different (a test of conditional independence for *nominal* factors in a 3-way table). e.g. I'd like to

I would like to do a SS type III analysis on a proportional odds logistic regression model. I use drop1(), but dropterm() shows the same behaviour. It works as expected for regular main effects models, however when the model includes an interaction effect it seems to have problems with matching the parameters to the predictor terms. An example: library("MASS"); options(contrasts =

Hi all, I've got some questions to post in regard to running asterisk in a production-grade environment, specifically targeting high-density IVR applications. No VoIP involved, just straight PSTN -> * and perhaps the occasional outdials or agent-based predictive dialing. 1) Which user would you run * under? 2) What other security-related issues do you have to resolve? 3) How do you handle

R Help on 'chisq.test' states that "if 'simulate.p.value' is 'TRUE', the p-value is computed by Monte Carlo simulation with 'B' replicates. In the contingency table case this is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are positive... In the

Hi, I''m looking for past efforts to integrate Rails and Needle. I am thinking of doing it myself but would be interested in seeing what others have done before. If there are examples of other IoC frameworks being used with Ruby I''d be interested in hearing about them too. I find IoC to be a helpful concept in general and, having glanced at a few existing Rails app.s, I

I'm trying to do a Hosmer-Lemeshow 'goodness of fit' test on my logistic regression model. I found some code here: http://sas-and-r.blogspot.com/2010/09/example-87-hosmer-and-lemeshow-goodness.html The R code is above is a little complicated for me but I'm having trouble with my answer: Hosmer-Lemeshow: p=0.6163585 le Cessie and Houwelingen test (Design library): p=0.2843620

hi, is there a way of calculating of measuring dependence between two categorical variables. i tried using the chi square test to test for independence but i got error saying that the lengths of the two vectors don't match. Suppose X and Y are two factors. X has 5 levels and Y has 7 levels. This is what i tried doing >temp<-chisq.test(x,y) but got error "the lengths of the two