similar to: anova with missing data (incomplete design)

Displaying 20 results from an estimated 10000 matches similar to: "anova with missing data (incomplete design)"

2010 Jun 29
1
Performance enhancement for ave
library(plyr) n<-100000 grp1<-sample(1:750, n, replace=T) grp2<-sample(1:750, n, replace=T) d<-data.frame(x=rnorm(n), y=rnorm(n), grp1=grp1, grp2=grp2) system.time({ d$avx1 <- ave(d$x, list(d$grp1, d$grp2)) d$avy1 <- ave(d$y, list(d$grp1, d$grp2)) }) # user system elapsed # 39.300 0.279 40.809 system.time({ d$avx2 <- ave(d$x, interaction(d$grp1, d$grp2, drop =
2017 Oct 31
0
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hi Arie, Thank you for your further research into the issue. Regarding Stata: On the other hand, JMP gives model matrices that use the main effects contrasts in computing the higher order interactions, without the dummy variable encoding. I verified this both by analyzing the linear model given in my first example and noting that JMP has one more degree of freedom than R for the same model, as
2011 Jan 31
2
identify subsets based on two grouping factors
Hi, I have a data.frame that has a categorical variable, for which I would like to look at the distribution of levels of this variable, based on a grouping of two other variables. As an example: x <- data.frame(obs=sample(c('low', 'high'),100, replace=TRUE), grp1=sample(1:10, 100, replace=TRUE), grp2=runif(100)) cut.grp1 <- cut(x$grp1, 3) cut.grp2 <- cut(x$grp2, 3)
2017 Nov 02
0
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hi Arie, The book out of which this behavior is based does not use factor (in this section) to refer to categorical factor. I will again point to this sentence, from page 40, in the same section and referring to the behavior under question, that shows F_j is not limited to categorical factors: "Numeric variables appear in the computations as themselves, uncoded. Therefore, the rule does not
2017 Nov 04
0
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hi Arie, I understand what you're saying. The following excerpt out of the book shows that F_j does not refer exclusively to categorical factors: "...the rule does not do anything special for them, and it remains valid, in a trivial sense, whenever any of the F_j is numeric rather than categorical." Since F_j refers to both categorical and numeric variables, the behavior of
2011 Jan 31
1
arranging pie charts in a matrix layout with row/col labels
Hi, I have a vector of data, that I group based on two factors via tapply. For each such grouping I would like to plot a pie chart. I can layout these pie charts in a matrix layout, correpsonding to the levels of the two factors. But I am getting stuck on how to label the rows and colums. My current approach looks like this: x <- data.frame(obs=sample(c('low', 'high'),100,
2017 Nov 06
0
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hi Arie, Given the heuristic, in all of my examples with a missing two-factor interaction the three-factor interaction should be coded with dummy variables. In reality, it is encoded by dummy variables only when the numeric:numeric interaction is missing, and by contrasts for the other two. The heuristic does not specify separate behavior for numeric vs categorical factors (When the author of
2009 Dec 10
1
Help with beanplot fromatting
Dear Helpful R Users, I am graphing some data using the beanplot, but I am having trouble getting the output I desire. I have five tanks (A-E) and 2 groups for each tank grp1 or grp2, except tank C where there is only grp1. (I only changed the grouprep to "C grp1" for the example) When I plot them, I would like A B C(only grp1 - half of the bean plot) then D and E (as full beans).
2004 Oct 22
1
ave gives unexpected NA's
[R 2.0.0 on Linux] I tried: > df <- data.frame( grp1=factor( c('A' ,'A' ,'A' ,'D', 'D' ) ) , grp2=factor( c('a1','a2','a2','d1','d1') ) ) > df grp1 grp2 val 1 A a1 1 2 A a2 2 3 A a2 4 4 D d1 8 5 D d1 16 I got: > with( df, ave( val, grp1, grp2, FUN=sum ) )
2018 Dec 05
1
Restricting sending mail to domain or group
On Wed, 5 Dec 2018, Alexander Dalloz wrote: >> I have a group alias (all at company.com). >> (1) Only company.com accounts should be able to send an email to everybody >> in that company via all at company.com. >> (2) - rather optional: refine the restrictions, e.g. two groups, >> grp1 at company.com and grp2 at company.com. Grp1 members should be able to send
2017 Oct 27
2
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hello Tyler, I want to bring to your attention the following document: "What happens if you omit the main effect in a regression model with an interaction?" (https://stats.idre.ucla.edu/stata/faq/what-happens-if-you-omit-the-main-effect-in-a-regression-model-with-an-interaction). This gives a useful review of the problem. Your example is Case 2: a continuous and a categorical regressor.
2011 Apr 07
1
plyr workaround to converting by() to a data frame
Dear all Is there a clean plyr version of the following by() and do.call(rbind, ...) construct: > df<-data.frame(a=1:10,b=11:20,c=21:30,grp1=c("x","y"),grp2=c("x","y"),grp3=c("x","y")) > dfsum<-by(df[c("a","b","c")], df[c("grp1","grp2","grp3")], range) >
2016 Jan 27
1
permissions problem
Hello, i'm using samba 4.1 on a debian stable, samba act as a NT4 PDC. i have a permission problem in a samba share. It's a public share where everybody can read/write and it works fine. In this share, there is a directory with "specials" permissions drwxrwx--- 20 root grp2 4096 nov. 16 14:36 Dossier For me, these permissions allows someone from "grp2" group to
2017 Nov 02
2
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hello Tyler, Thank you for searching for, and finding, the basic description of the behavior of R in this matter. I think your example is in agreement with the book. But let me first note the following. You write: "F_j refers to a factor (variable) in a model and not a categorical factor". However: "a factor is a vector object used to specify a discrete classification"
2011 Feb 08
2
Convert the output of by() to a data frame
I'd like to summarize several variables in a data frame, for multiple groups, and store the results in a data.frame. To do so, I'm using by(). For example: df<-data.frame(a=1:10,b=11:20,c=21:30,grp1=c("x","y"),grp2=c("x","y"),grp3=c("x","y")) dfsum<-by(df[c("a","b","c")],
2018 Dec 05
6
Restricting sending mail to domain or group
Hi folks, has anybody a simple solution for the following request? I have a group alias (all at company.com). (1) Only company.com accounts should be able to send an email to everybody in that company via all at company.com. (2) - rather optional: refine the restrictions, e.g. two groups, grp1 at company.com and grp2 at company.com. Grp1 members should be able to send mails to grp2 but not vice
2013 Sep 26
1
Less than equal to symbol in ggplot2 legend text
Hello, I am trying to add a less than equal to symbol in a ggplot2 legend text. See sample code below. I have tried using the expression function and \u2264. I also tried adding labels to legend.text under theme. Neither of these 3 options work. Please help, Mahesh ++++++++++++++ Extra.column=ifelse(data[,covariate]>cutpoint,1,0) Grp1 <- "\u2264 1.5" Grp2 <-
2008 Aug 18
3
Samba 3.0.x access rights issue with secondary groups or Unix rights
Hi experts I have a trouble in access rights I am running Samba 3.0.31 on Solaris 10 x86 64 bits as member server of an Active Directory 2003 R2 domain (MYDOMAIN) using Identity Management for Unix I set rights to access a sub folder of a Samba share. On Solaris the user "toto" jdoe can write a new file. From Windows, the same user can't. Itlooks like OK when the primary group
2017 Nov 04
2
Bug in model.matrix.default for higher-order interaction encoding when specific model terms are missing
Hello Tyler, I rephrase my previous mail, as follows: In your example, T_i = X1:X2:X3. Let F_j = X3. (The numerical variables X1 and X2 are not encoded at all.) Then T_{i(j)} = X1:X2, which in the example is dropped from the model. Hence the X3 in T_i must be encoded by dummy variables, as indeed it is. Arie On Thu, Nov 2, 2017 at 4:11 PM, Tyler <tylermw at gmail.com> wrote: > Hi
2010 Aug 11
2
help to polish plot in ggplot2
Hi, I wanted to generate a plot which is almost like the plot generated by the following codes. category <- paste("Geographical Category", 1:10) grp1 <- rnorm(10, mean=10, sd=10) grp2 <- rnorm(10, mean=20, sd=10) grp3 <- rnorm(10, mean=15, sd=10) grp4 <- rnorm(10, mean=12, sd=10) mydat <- data.frame(category,grp1,grp2,grp3,grp4) dat.m <- melt(mydat) p <-