similar to: ANOVA/aov question

Hi, I'm new to R (though I have spent hours trying to learn how to use it) and also not very knowledgeable about statistics, so I hope you will excuse what may seem like a very basic question. I'm trying to use R to do an ANOVA analysis for some data with an unbalanced design, and while I was trying to figure that out, I got confused about the purpose of the "lm". All

All, I'm relatively new to using R, having used it thus far for some simple statistics and plotting. However, I'm not new to programming by any measure. I've been looking at the various modules available for clustering, factor analysis, etc. and find that I need advice on which modules I should be focusing on and their application. I have a data set comprised of columns of both

Hello, My name is Dontrece Smith. I am creating figures for my GAMs. I change my qualitative variables to 1 or 2 in my dataset, so I would be able to run my GAMs. However, R will only display plots for my quantitative variables and not my qualitative variables. Is there any way to fix this issue? I listed some of my code below: > library(mgcv) This is mgcv 1.7-13. For overview type

Hello, I'm a R newcomer and I'm wondering the kind of data structure that would best fit to my problem: my data are equities (stocks) : so I have a time serie (say 1 year of weekly data), and a bunch of qualitative + quantitative variables : the sector of the stock (biotech/finance...), the geographical region, the name, ISIN code, P/E ratios, whatever... The data.frame is perfect for the

RDQA is a package for Qualitative Data Analysis built upon R. It works both on the Windows and Linux/FreeBSD platforms. RQDA is an easy-to-use tool to assist in the analysis of textual data. At the present, it supports only plain text format data. All the information is stored in SQLite database via the R package of RSQLite. The GUI is based on RGtk2, via the aid of gWidgetsRGtk2. It includes a

RDQA is a package for Qualitative Data Analysis built upon R. It works both on the Windows and Linux/FreeBSD platforms. RQDA is an easy-to-use tool to assist in the analysis of textual data. At the present, it supports only plain text format data. All the information is stored in SQLite database via the R package of RSQLite. The GUI is based on RGtk2, via the aid of gWidgetsRGtk2. It includes a

Hi, I have some doubt about how qualitative factors are coded in R. For instance, I consider a response y, a quantitative factor x and a qualitative factor m at 3 levels, generated as follow : y_c(6,4,2.3,5,3.5,4,1.,8.5,4.3,5.6,2.3,4.1,2.5,8.4,7.4) x_c(3,1,3,1,2,1,4,5,1,3,4,2,5,4,3) m_gl(3,5) lm(y~x+m) Coefficients: (Intercept) x m2 m3 3.96364 0.09818

Hello list members, this is rather a simple question but I can't find the solution myself, so I would appreciate your help and I apologise in advance for my ignorance. I have a data frame with a header containing variable names and I have 4 independent variables and 5 dependent variables. It looks like this: x1 x2 x3 x4 y1 y2 y3 y4 y5 1 1 33 55 4

When I load a table from a data source and run summary() on it, the summary gives me basic summary statistics I'm looking for, and it also discriminates between quantitative and qualitative data and summarizes them accordingly. For example, if I do this: mydata <- read.table("data.txt") summary(mydata) I would get output like this: > summary(mydata) County

Hi! Apologies if this is not the correct place to ask. I am attempting a MFA analysis of a dataset based on wine chemical and sensory analysis, based on the STHDA tutorial [1]. (I am using this dataset here too, as an example dataset to work on without posting my actual data. I've tried this with both my data and the example data, with the exact same results.) The only issue I am having is

Does anyone know of a test for stationarity of a time series, or like all ordination techniques it is a qualitative assessment of a quantitative result. Books, papers, etc. suggestions welcome. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are

Hello, i have this dataset http://www.umass.edu/statdata/statdata/data/pharynx.txt. the variables GRADE, T_STAGE anda N_STAGE are qualitative or quantitative variables??? i only have this simple doubt...! another example: why in the dataset ovarian (library survival) the variable ecog.ps: ECOG performance status (1 is better, see reference) it is consider quantitative? Thank's for

Hello everybody! I've a file with several data six variables, three quantitative and three qualitative, I would like to select a group of data from the file to analyze then, i.e: my file is like that (but with 6 variables): Var1 Var2 2 1 5 1 8 1 7 2 3 2 8 2 I want to use only the data where var2 is "1" 2 1 5 1 8 1 Exist a

Hello, I apologize that this is off-topic. I am seeking information on perception of graphical data, in an effort to improve the plots I produce. Would anyone point me to literature reviews in this area? (Or keywords to try on google?) Is this located somewhere near cognitive science, psychology, human factors research? For example, some specific questions I have are: I recall as a child

Dear all, I hope to be the clearest I can. Let's say I have a dataset with 10 variables, where 4 of them represent for me a certain phenomenon that I call Y. The other 6 represent for me another phenomenon that I call X. Each one of those variables (10) contains 37 units. Those units are just the respondents of my analysis (a survey). Since all the questions are based on a Likert scale, they

HI!!! I have a table containing qualitative and quantitative data; one of the columns contains "Level of education", and the possibilities are "none", "High school", "college"; I want to give the value 0 to "none", the value 1 to "High school", and 2 to "college", but I got the following error: In `[<-.factor`(`*tmp*`,

Dear all: My logistic regression model includes one qualitative and one quantitative predictor variable, aes <- glm(p.a ~ spp * log(light), family=binomial(link=logit)), where spp is abundance of 3 species and light is subcanopy light availability varying from 0 1. I want to test differences among levels of the quantitative variable at a value of x other than the current log(light)=0.

I am trying to use R lm() with quantitative and qualitative predictors, but am getting different results than those that I get in SAS. In the R ANOVA table documentation I see that "Type-II tests corresponds to the tests produced by SAS for analysis-of-variance models, where all of the predictors are factors, but not more generally (i.e., when there are quantitative predictors)." Is

I've found RColorBrewer useful for its qualitative palettes, but wished that it could generate more than 12 qualitative palettes (e.g. with Set3). Any suggestions for alternative color palette generators that can handle e.g. 18 distinctive colors? (I'm aware of using rainbow(), but this doesn't generate enough distinct colors when the number of palettes is large). Thanks, Andrew

HI! I am working with a table with quantitative and qualitative data; one of the columns is "Level of education", which is an ordered factor. I want to get rid of the ordered factor, and set my own scale. How to do that? All the time I get the following error: In `[<-.factor`(`*tmp*`, educa = "Less than high school", value = 3) : invalid factor level, NAs generated