similar to: categorical vs numerical

can you do Logistic regression in R, if so how do you do it and how do you test the fit of a model? -- View this message in context: http://n4.nabble.com/Logistic-regression-tp1059870p1059870.html Sent from the R help mailing list archive at Nabble.com.

Is this book worth its dollar? If so, why?, if not, why not? Cheers. -- View this message in context: http://n4.nabble.com/Ggplot2-Elegant-Graphics-for-Data-Analysis-Use-R-2009-Paperback-tp931702p931702.html Sent from the R help mailing list archive at Nabble.com.

Dear all - With the following code I get Boxplots and Stripcharts in one Plot: with(InsectSprays, boxplot(count ~ spray, boxwex = 0.3)) with(InsectSprays, stripchart(count ~ spray, col = "red", vertical = TRUE, add = TRUE)) But the dots from the stripchart are plotted over the Boxes. Is there any possibility to have Stripchart and Boxplots side-by-side, i.e. to move boxplots and/or

Hello, I''ve looked around and I can't seem to find a package to do data mining in R for a mixture of categorical and numerical attributes. If you have this data set: ## dummy data set.seed(123) dummy <- data.frame(A = sample(paste("tasks",1:100), 10000,B = sample(paste("loads",1:100), 10000, replace = TRUE), B =

Dear R users, if all my numerical variables in my datasets having the same units, may I leave them unnormalized, just do cv.glmnet directly(cv.glmnet(data,standardize=FALSE))? i know normally if there is a mixture of numerical and categorical , one has to standardize the numerical part before applying cv.glmnet with standardize=fase, but that's due to the different units in the numerical

Hello there. Is there any function in R that can do cluster on a set of data that has both categorical and numerical variables? thanks. siangli

I want to make illustrations a la boxplot for a data material with several groups. Some of the groups are very small, so a boxplot doesn't make sense. I would like to use stripchart for these groups. On the other hand, some of the groups are very large, so for them stripchart isn't so good. So my question is: Is it possible to combine boxplots and and stripcharts in one figure? (Of course,

I am trying to perform cluster analysis on survey data where each respondent has answered several questions, some of which have categorical answers ("blue" "pink" "green" etc) and some of which have scale answers (rating from 1 to 10 etc).My problem is that certain age groups were over-sampled and I need to weight the data collected in order to accurately reflect the

Hi R help, Hi R help, Which is the easiest (most elegant) way to force "aov" to treat numerical variables as categorical ? Sincerely, Andrea Bernasconi DG PROBLEM EXAMPLE I consider the latin squares example described at page 157 of the book: Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter. This example use

Whats happening? everthings changing round here...plus alot less posts/users.. -- View this message in context: http://n4.nabble.com/Whats-happening-to-the-forum-tp913858p913858.html Sent from the R help mailing list archive at Nabble.com.

Hi everybody, I'm a new member of the list. I'm just starting to use R. I'm looking for information about stripcharts. I didn't find a lot on the web. Outside http://www.maths.lth.se/help/R/.R/library/graphics/html/stripchart.html there isn't much I found. I'm trying to create three vertical stripcharts "glued" to one another. I succeeded to create one

Dear All, Can the x matrix in the glmnet() function of glmnet package be a data.frame with numeric columns and factor columns? I am asking this because I have a model with both numeric and categorical predictors, which I would like to study with glmnet. I have already tried to use a data.frame, but with no success -- as far as I know, the matrix object can only have data of a single type. Is

I need to find out the difference between the way R calculates weighted regression and standard regression. I want to plot a 95% confidence interval around an estimte i got from least squares regression. I cant find he documentation for this ive looked in ?stats ?lm ?predict.lm ?weights ?residuals.lm Can anyone shed light? thanks Chris. -- View this message in context:

I currently have a data set in which gender is inputed as "Male" and "Female" , and I'm trying to convert this into "1" and "0". I found a website which reccomended using two commands: data$scode[data$sex=="M"] <- "1" data$scode[data$sex=="F"] <- "2" to convert to numbers, and: data$scode <-

I am looking to fit one or more latent categorical variables to data that is a mixture of categorical and continuous variables. Factor analysis would work for continuous data, latent class analysis for categorical data. I understand that in a package such as MPlus I could perform a single analysis of both data types. Are there similar routines available in R? Stuart -----Original Message-----

Dear Metafor users, I''d like to test a model with 2 continuous and 2 categorical moderators in a meta regression. One categorical parameter has 2 levels and the other has 4 levels. If I understand correctly, when I include all moderators in the model, Metafor returns main effects of the continuous parameters and contrasts of each level of categorical moderators with the intercept (which

Are there any suitable routines that perform factor analysis of categorical or mixed categorical/continuous data in R? Stuart Dr Stuart Leask MA MB BChir (Cantab) MRCPsych Clinical Lecturer in Psychiatry, University of Nottingham Dept Psychiatry Duncan Macmillan House, Porchester Road, Nottingham. NG3 6AA. UK tel. 00 44 115 969 1300 xtn 40784 fax 0115 955 5352

Hello, I wanted to do the multiple regression on categorical predictor data there's variable x1,x2,x3 and x3 is categorical one. so i just used as.factor(x3) and then ran multiple regression is it a good way to do the multiple regression on categorical predictor data? and how can I interpret the estimates? also if using as.factor is a good way, is there any difference with doing dummy coding

Hi All: I am working on a dataset of a study on healthcare workers. One of the variables I am studying is a categorical variable (variable name:EDUC, indicates educational achievement, with 6 levels: "illiterate", "primary", "junior high school", "high school completed", "undergraduate", and "postgraduate"). I want to collapse the

Hello R folks, I am encountering a problem with the following scatterplot function from the car package: > scatterplot(y~x|z) where y and x are continuous (interval) random variables and z is a categorical variable. When z is a categorical variable coded 1 or 2, I (appropriately) get a scatterplot of y by x, coded by z. Similarly, when z is a categorical variable coded 1, 2, or 3, there is