similar to: Treatment-Contrast Interactions

Hello all, I have a data frame with the following columns: timestamp, activity, interval. Each row contains information about an activity that occured over a time interval. "Timestamp" is when the interval ended, "Activity" is a factor that represents the type of activity, and "Interval" is a double which represents an interval in time. The data frame is sorted

Hello all, Simple version of my problem: I've got a list of data frames, where each data frame has the same number of columns and the same column names. I'd like to flatten the list into one large data frame. Is there an easy way to do this? Quick example code: a <- data.frame(x=c(1,2,3),y=c(5,7,9) b <- data.frame(x=c(2,4,7,9),y=c(2,3,5,4)) z <- list(a,b) # Do

Hello: I''m trying to put a puppet master on an EC2 instance, and have it be accessible to agentes using either its EC2 DNS name (e.g., ec2-xxx-xxx-xxx-xxx.compute-1.amazonaws.com) or a friendlier alias (e.g., puppet.example.com). My /etc/puppet/puppet.conf looks like: [master] certname=ec2-xxx-xxx-xxx-xxx.compute-1.amazonaws.com

Dear list, I am confused on how to explain the interaction term in the context of "treatment contrast". for example, I have an data frame as below: sub group val 1 a group1 3.685625 2 a group1 3.407445 3 a group1 4.040920 4 a group1 2.890875 5 b group1 3.853280 6 b group1 4.113585 7 b group1 3.043250 8 b group1 3.800920 9 c group1 5.394305 10 c

glm(A~B+C+D+E+F,family = binomial(link = "logit"),data=tre,na.action=na.omit) Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : contrasts can be applied only to factors with 2 or more levels however, glm(A~B+C+D+E,family = binomial(link = "logit"),data=tre,na.action=na.omit) runs fine glm(A~B+C+D+F,family = binomial(link =

Why is RH using such an outdated version of OpenSSL ? I understand that they may have back-ported the fix but I just tried installing Net::SSLeay on a Centos 3.3 box and it wouldn't install, saying that the openssl version was old and suggested I get 9.7b or later? How are you handling this problem? I am resorting to recompiling OpenSSL 9.7d . Thanks, Dave

Dear list members, I have a 2-factor ANOVA where the summary.lm output looks like this (using treatment contrasts): Value Std. Error t value Pr(>|t|) (Intercept) 0.0389 0.0220 1.7695 0.0817 as.factor(Block)1 0.0156 0.0066 2.3597 0.0215 as.factor(Block)2 -0.0018 0.0037 -0.4857 0.6289 as.factor(Block)3 -0.0007 0.0026 -0.2812 0.7795

Hello, R experts, Sorry for asking this question again again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

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I was trying to do a bunch of planned contrast but ran into a snag. fit.contrast won't work with an Error term in aov. Ok, then I use lme. Only, now it seems there is no way to enter the interaction terms (something like "x1:x2"). I couldn't find a way to use the interaction term in the help. Is there an undocumented method or some other command for planned contrasts?

Hi! I try to explain the efffect of (1) forest where i took samples's soils (* Lugar*: categorical variable with three levels), (2) nitrogen addition treatments (*Tra*: categorical variable with two levels) on total carbon concentration's soil samples (*C: *continue* *variable) during four months of sampling (*Time:* categorical and ordered variable with four levels). I fitted the

?contrast in the contrast package gives me the following description. However, I have no idea what Type II and III contrasts are. Could somebody explain it to me? And what does 'type' mean here? *?type?*: set ?type="average"? to average the individual contrasts (e.g., to obtain a Type II or III contrast)

Hello, I've got what I'd expect to be a pretty simple issue: I fit an aov object using multiple error strata, and would like some significance tests for the contrasts I specified. In this contrived example, I model some test score as the interaction of a subject's gender and two emotion variables (angry, happy, neutral), measured at entry to the experiment (entry) and later

Hi, For a n-level factor, I'd like to specify the first contrast and have the remaining n-2 constructed automatically so that the set is orthogonal. I then test the contrasts with summary.lm(anova-object). In S-Plus, the following works: >y.anova <- aov( y ~ C(CO2,c(1,0,-1)) ) >summary.lm(y.anova) In R, it fails with the following error: >levels(CO2) [1]

Could anyone please explain how to set up contrasts between means in R. I want to know if "before I conduct an experiment and believe the mean for 1 and 2 will be different from means 3 and 4, Is this true?" That is what I have to prove or disprove, I thought that contrasts would be the way to go. Thanks for the help. Igor [[alternative HTML version deleted]]

Hi all, I have been trying to reproduce an analysis from Douglas Montgomery?s book on design and analysis of experiments. Table 6.10 of example 6.2 on page 246, gives a table as follows: > NPK <- expand.grid(A=mp,B=mp,C=mp,D=mp) > Rate <- c(45,71,48,65,68,60,80,65,43,100,45,104,75,86,70,96) > filtration <- cbind(NPK,Rate) > filtration A B C D Rate 1 - - - - 45 2

Hi all, Hopefully this is an easy question and I've overlooked something simple. I want to present specific contrasts in an ANOVA table. I can of course get the significance tests with summary.lm, but my adviser wants the results in ANOVA format. Here is a minimal example: > x <- factor(c(rep("condition.1", 5), rep("condition.2", 5), rep("condition.3", 5)))

I'd like to make a less than full rank design using dummy variables for factors. Here is some example data: when <- data.frame(time = c("afternoon", "night", "afternoon", "morning", "morning", "morning", "morning", "afternoon", "afternoon"),

How do we specify a contrast interaction matrix for an ANOVA model? We have a two-factor, repeated measures design, with Cue Direction (2) x Brain Hemisphere(2) Each of these has 2 levels, 'left' and 'right', so it's a simple 2x2 design matrix. We have 8 subjects in each cell (a balanced design) and we want to specify the interaction contrast so that: CueLeft>CueRght