similar to: using categorical variable in multiple regression

how can I compute partial correlation there's four variables; income, age, educational level, race. income is indenpendent variable and race is nominal variable I want to calculate partial correlation or semi-partial correlation between income & race help me out... thanks. -- View this message in context: http://r.789695.n4.nabble.com/partial-correlation-tp3591520p3591520.html Sent

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

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-----

It is unclear to me how aov() handles non-categorical variables. I mean it works and produces results that I would expect, but I was under impression that ANOVA is only defined for categorical variables. In addition, help(aov) says that it "call to 'lm' for each stratum", which I presume means that it calls to lm() for every group of the categorical variable, however I

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

I am running the ctree function in R. My data has about 10 variables, many of which are categorical. 2 of the categorical variables have many levels (one has 900 levels, another has 1,000 levels). As an example, 1 of these variables is disease code and is structured as A, B, C, ...., AA, AB, AC.... Each time i've tried to run the ctree function, including these 2

Dear all, I have a question about using categorical predictors for SVM, using "svm" from library(e1071). If I have multiple categorical predictors, should they just be included as factors? Take a simple artificial data example: x1<-rnorm(500) x2<-rnorm(500) #Categorical Predictor 1, with 5 levels x3<-as.factor(rep(c(1,2,3,4,5),c(50,150,130,70,100))) #Catgegorical Predictor

Hello, I am working in a longitudinal study, with a categorical variable as a dependent variable (alcohol consumption: no use, use, abuse and dependence) with repeated measures (baseline, 1 year, 2 years). Besides I have another variable with two groups: control and experimental. I would like to analyze the evolution in each group, I have though in lme, but I am not sure if I can do an lme with

Dear helpers I constructed a data frame with this structure > str(dados1) `data.frame': 485 obs. of 16 variables: $ Emissor : int 1 1 1 1 1 1 1 1 1 1 ... $ Marisca.Rio : int 1 1 1 1 1 1 1 1 1 1 ... $ Per?odo : int 1 1 1 1 1 1 1 1 1 1 ... $ Reproducao : int 3 3 3 3 3 3 3 3 3 3 ... $ Estacao : int 2 2 2 2 2 2 2 2 2 2 ... $ X30cm : int

I would appreciate help in knowing how to repeat categorical variable code given in column=A, by the number in a matching column=B. For example, I have a categorical variable code attributed to a household=A and want to replicate the code for all member of the household, as given in column=B. I would like to have one sequence of categorical variable codes for individuals in column C. I have ~9000

Dear users, In my psychometric test i have applied logistic regression on my data. My data consists of 50 predictors (22 continuous and 28 categorical) plus a binary response. Using glm(), stepAIC() i didn't get satisfactory result as misclassification rate is too high. I think categorical variables are responsible for this debacle. Some of them have more than 6 level (one has 10 level).

Hello: I am new to R and am going through the growing pains, wonder if you could help alleviate some. I wished to find the estimate for a categorical variable without it being broken into levels but dont know how to. if I use the following example: $>data(iris) $>g=lm(Sepal.Length~.,iris) $>summary(g) I get the estimate of the categorical variable "Species" broken up into

Hi I would like to analyse an ordinal categorical variable. I know how I can analyse a nominal categorical variable (with multinom or if there are only two levels with glm). Does somebody know which command I need in R to analyse an ordinal categorical variable? I want to describe the variable y with the variables x1,x2,x3 and x4. So my model looks like: y ~ x1+x2+x3+x4. y: ordinal factor

Dear metafor users, I am working on a meta-analysis of reliability and the correlation associations. I need some help about conducting categorical moderators variables. Questions 1: How to conduct the weighted ANOVAs assuming a mixed-effects model on the tranformed alpha coefficients/the tranformes correlation coefficients for the categorical moderator variables? Questions 2: How to

Dear R-list, I have two variables (numerical and categorical) and would like to have the sum (and maybe some other statistics) of the numerical variable by the categorical one. Can you help me, Thank you, Fabrizio --------------------------------------------------------------- Fabrizio De Amicis IT Department Generali Information Technologies - (GIT) Centro Galleria 2, Via Cantonale CH -

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

Hi, Suppose a binomial GLM with both continuous as well as categorical predictors (sometimes referred to as GLM-ANCOVA, if I remember correctly). For the categorical predictors = indicator variables, is then there a suggested minimum frequency of each level ? Would such a rule/ recommendation be dependent on the y-side too ? Example: N is quite large, a bit > 100. Observed however are

Hello All: I know the function loglin() and loglm() from librarary(MASS) performs analysis on nominal categorical data. Are there any libraries, functions or examples available for analysis of ordinal categorical data? I have in mind procedures that can replicate results in Alan Agresti (1984) "Analysis of Ordinal Categorical Data." Thanks, ANDREW

I have two questions: 1. If I want to do a binomial logit, how to handle the categorical response variable? Data for the response variables are not numerical, but text. 2. What if I want to do a multinomial logit, still with categorical response variable? The variable has 5 non-numerical response levels, I have to do it with a multinomial logit. Any input is highly appreciated! Thanks! Ed