search for: factor3

...ve extensively searched the internet and have I missed something obvious, it was due to # tiredness and not to lazyness. # Some dummy data: mydata<- data.frame(factor1 = factor(rep(LETTERS[1:6], each = 80)), factor2 = factor(rep(c(1:5), each = 16)), factor3 = factor(rep(c(1:4), each = 4)), var1 = rnorm(120, mean = rep(c(0, 3, 5), each = 40), sd = rep(c(1, 2, 3), each = 20)), var2 = rnorm(120, mean = rep(c(6, 7, 8), each = 40), sd = rep(c(1, 2, 3), each = 20))) # Splitting data i...

Hi All, I have a 4-dimensional data. I'm using barchart() function from lattice package. The R code and data are below - code includes one for stack=TRUE and other for stack=FALSE. I would like to present the data in another form which would be plotting Factor3 levels (P, Q, R, S) as two stacked bars (side by side). Like, for each level of Factor1 there should be two bars: first bar showing stacked values of "P" and "Q" and the adjacent bar showing stacked values of "R" and "S". Is it possible using barchart() funct...

...quot;, "A", "B" instead of alphabetical. My normal methods do not work. with kind regards Anna Zakrisson # Some dummy data: mydata<- data.frame(factor1 = factor(rep(LETTERS[1:6], each = 80)), factor2 = factor(rep(c(1:5), each = 16)), factor3 = factor(rep(c(1:4), each = 4)), var1 = rnorm(120, mean = rep(c(0, 3, 5), each = 40), sd = rep(c(1, 2, 3), each = 20)), var2 = rnorm(120, mean = rep(c(6, 7, 8), each = 40), sd = rep(c(1, 2, 3),...

Full_Name: Mike Ulrich Version: 2.9 OS: Mac OSX Submission from: (NULL) (69.169.178.34) The help documentation for loadings() lists more then one parameter. The function call only expects one parameter. The digits, cutoff, and sort parameters are not used in the function. ## S3 method for class 'loadings': print(x, digits = 3, cutoff = 0.1, sort = FALSE, ...) ## S3 method for class

...473451 #v6 0.4086076 0.4326113 0.4320310 0.4323259 0.9473451 1.0000000 factanal(m1, factors=3) # varimax is the default # Output from R #Call: #factanal(x = m1, factors = 3) #Uniquenesses: # v1 v2 v3 v4 v5 v6 #0.005 0.101 0.005 0.224 0.084 0.005 #Loadings: # Factor1 Factor2 Factor3 #v1 0.944 0.182 0.267 #v2 0.905 0.235 0.159 #v3 0.236 0.210 0.946 #v4 0.180 0.242 0.828 #v5 0.242 0.881 0.286 #v6 0.193 0.959 0.196 # Factor1 Factor2 Factor3 #SS loadings 1.893 1.886 1.797 #Proportion Var 0.316 0.314 0.300 #Cumulative Var 0.31...

Hi All, I have googled and tried finding if someone has ever tried producing (Grouped + Stacked) Barplot. I couldn't find one. My data needs to be reshaped, but once it is done it would be something like this: Factor1 Factor2 Factor3 Value A X P 10 A X Q 20 A Y P 20 A Y Q 5 A Z P 20 A Z Q 10 B X P 20 B X Q 10 B Y P 30 B Y Q 50 B Z P 10 B Z Q 20 There are three categorical variables (Factor1, Factor2, and Factor3 havin...

...of minimum values from groups in another data set. The following almost does what I want. (Note, I'm using the word factor differently from it's meaning in R; bad choice of words) myframe = data.frame(factor1 = rep(1:2,each=8), factor2 = rep(c("a","b"),each=4, times=2), factor3 = rep(c("x","y"),each=2, times=4), y=1:16) attach(myframe) minimums = by(y, list(factor1, factor2,factor3), min) detach(myframe) The problem is that "minimums" is object of class "by", which looks like some kind of array with the number of dimension equal to...

...me help in the followings: I'm doing factor analysis and I need to extract the loading values and the Proportion Var and Cumulative Var values one by one. Here is what I am doing: > fact <- factanal(na.omit(gnome_freq_r2),factors=5); > fact$loadings Loadings: Factor1 Factor2 Factor3 Factor4 Factor5 b1freqr2 0.246 0.486 0.145 b2freqr2 0.129 0.575 0.175 0.130 0.175 b3freqr2 0.605 0.253 0.166 0.138 0.134 b4freqr2 0.191 0.220 0.949 b5freqr2 0.286 0.265 0.113 0.891 0.190 b6freqr2 0.317 0.460 0.151...

...so i hope to get some valuable insights from you. i run an ANOVA with four factors; factor4 is an between factor (two different groups measured), the others are withins (tested across /all/ subjects). accordingly, my model looks as follows: fm1 <-aov(dataSubjects~(factor1*factor2*factor3*factor4)+Error(subject/(factor1* factor2*factor3))+factor4,data=mydata) print(summary(fm1)) so far so good. i now would like to perform multiple comparisons, but separately for each level of factor4 (two). this is how I do it: i sort out (using subset) the levels im interested in co...

...1,1,1,6,4,5) v6 <- c(1,1,1,2,1,3,3,3,4,3,1,1,1,2,1,6,5,4) m1 <- cbind(v1,v2,v3,v4,v5,v6) myfac <- factanal(m1, factors=3, scores="regression")# cor(myfac$scores) *********************************************** Tells me Factor1 Factor2 Factor3 Factor1 1.000000000 0.001624383 0.002862785 Factor2 0.001624383 1.000000000 0.001956953 Factor3 0.002862785 0.001956953 1.000000000 which means that factor correlations are indeed quite low with regard to interpretation issues, but an analysis of a larger dataset yielded factor intercorrelations...

...Uniquenesses: height arm.span forearm lower.leg weight 0.127 0.005 0.193 0.157 0.090 bitro.diameter chest.girth chest.width 0.359 0.411 0.490 Loadings: Factor1 Factor2 Factor3 height 0.886 0.267 -0.130 arm.span 0.937 0.195 0.280 forearm 0.874 0.188 lower.leg 0.877 0.230 -0.145 weight 0.242 0.916 -0.106 bitro.diameter 0.193 0.777 chest.girth 0.137 0.755 chest.width 0.261 0....

...= na.omit) Uniquenesses: yrelerr.PathRot relerr.Yaw relerr.PathRel.Orn Spat Orn FD 0.005 0.163 0.587 0.005 0.005 0.005 Loadings: Factor1 Factor2 Factor3 yrelerr.PathRot 0.483 0.871 relerr.Yaw 0.910 relerr.PathRel.Orn -0.473 -0.233 0.368 Spat 0.983 0.167 Orn 0.168 0.982 FD 0.949 0.147 0.271 # for Modality==Vis: Uniquenesses: yrelerr.PathRot relerr.Y...

...w to R, I have been using SAS for a while. Not surprisingly, I find R much better in graphics, which is publication ready right away. Recently, I have been trying to calculate some basic statistics using R. I have a dataset of multiple rows per subject. For example: Subject Date Factor1 Factor2 Factor3 P1 0.5 1 1 3 P1 1 3 2 5 P1 2 3 5 NA ... P2 0.5 1 6 4 P2 1 2 NA 7 P2 2 3 1 2 ... I wanted to get the 'by subject' statistics of the factors. I used the following code: a=by(dat1, dat1$Subject, mean, na.rm=TRUE) - this is for a mean. However, when I try that with a 'median', I get...

Dear list members, I apologize for putting this (probably) very basic question on the mailing list. I have scanned through the R website (using search) but did not found an answer. (code included below) A factor matrix is simply extracted (which can then subsequently be exported using write.table) by FACT$loadings[1:6,]. I would also like to specifically extract and export

I am having difficulty obtaining the scores from my principal component analysis. I have used this method before and have had no problems. The data set that I am using this time is similar to what I have used in the past. What do I need to do to my dataset in order for me to obtain these scores? R screen says the following message Error in factanal(covmat = pasa.cov, factors = 4) :

Dear list, I'm having second thoughts after solving a very trivial problem: I want to extend the relevel() function to reorder an arbitrary number of levels of a factor in one go. I could not find a trivial way of using the code obtained by getS3method("relevel","factor"). Instead, I thought of solving the problem in a recursive manner (possibly after reading

This might be easy but I'm very new to R and this question doesn't seem to have any nice keywords that bring up relevant search results when I search the CRAN search engine. Therefore, I'll plead (as I have in the recent past) Newbie status. I have a data frame with two factors (Factor 1 and 2) which together specify another unique level. I want to create a third factor in the

...uot;M") * (TEST1[[3]]=="1") ) * (TEST1[[4]]=="2X2"), ]) *********************************************************************************************************************************************************** Desired Output format (or something simlar): Factor1 Factor2 Factor3 Factor4 Intercept M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1) 20232 x x x x x x x x x x x x 2) B x x x x x x x x x x x x 3) E...

Dear list, i am setting up a GLM for a repeated measurement ANOVA using the lm and ANOVA function. my design contains four factors with 5, 5, 2 and 2 (= 14) levels, respectively. the data are stored in a data.frame with six columns, one for the data themselves and the remainings for the factors where strings indicate the factor levels in each row. now i would like to restructure this

hy guys i have one question :) i have two vectors markets and price market <- c(1, 5, 7, 9, 9, 6, 5, 4, 4, 3, 1, 2, 1) price <- c(100, 20, 30, 10, 50, 23, 23, 33, 96, 6, 4, 38, 96) i would like sum prices: market 1: (100+4+96), market 2: (38),..., market 9: (10+50) ao i would like get this result: (200, 38, ..., 60) and i don't wanna use while, for loops... is there any other function