similar to: two-way anova help

Dear friends, I have asked last few days about cross-random effects using PQL, but I have not receive any answer because might my question was not clear. My question was about analysing the salamander mating data using PQL. This data contain cross-random effects for (male) and for (female). By opining MASS and lme library. I wrote this code sala.glmm <- glmmPQL(fixed=y~WSf*WSM,

Hello R list, I am hoping to conduct a logistic regression with repeated measures, and would love an actual "code run through" for such an analysis. I found only one related post on this list, but a full answer was never provided. I understand that the routine lmer (or lmer2) in the lme4 package is often recommended in such a case, but actually implementing it is where I've hit a

Dear WizaRds, unfortunately, I have been unable to replace the '99' and '999' entries in library(UsingR) attach(babies) as definitions for missing values NA, because sometimes the 99 entry is indeed a correct value. Usually, or so I thought, NAs can easily replace a, say, 999 entry via mymat[mymat==999] <- "yodl" in a matrix or data frame. Alas, the babies'

Hi, I am attempting to plot survival curves estimated by cox proportional hazards regression model. The formula for the model is this: F.cox.weight <- coxph(Surv(Lifespan, Status) ~ MS + Weight + Laid + MS:Laid + Weight:Laid, data = LongF) MS = Mating status (mated/virgin) Weight = adult female weight, continuous covariate Laid = number of eggs laid by each female, continuous covariate I

Hi, I'm trying to work through a Nested ANOVA for the following scenario: 20 males were used to fertilize eggs of 4 females per male, so that female is nested within male (80 females used total). Spine length was measured on 11 offspring per family, resulting in 880 measurements on 80 families. I used the following two commands: summary(aov(Spinelength ~ Male*Female)) and

Greetings, I have a question that I'd like to get input on. I have a classic toxicology study where I artificially fertilized and exposed embryos to a chemical and counted defects. In addition, I kept track of male-female pairs that I used to artificially fertilize and generate embryos with. I need to use logistic regression to model the response, but also check that the genetics of the

Hello, I think I am beginning to understand what is involved in the so-called "Type-I, II, ..." ANOVAS (thanks to all the replies I got for yesterday's post). I have a question that will help me (and others?) understand it better (or remove a misunderstanding): I know that ANOVA is really a special case of regression where the predictor variable is categorical. I know that there

Hi, I'm sure this is simple, but I haven't been able to find this in TFM, say I have some data in R like this (pasted here: http://pastebin.com/raw.php?i=sjS9Zkup): > head(df) gender age smokes disease Y 1 female 65 ever control 0.18 2 female 77 never control 0.12 3 male 40 state1 0.11 4 female 67 ever control 0.20 5 male 63 ever state1 0.16

I am transitioning from SAS to R and am struggling with a relatively simple analysis. Have tried Venables and Ripley and other guides but can't find a solution. I have an experiment with 12 tanks. Each tank holds 10 fish. The 12 tanks have randomly assigned one of 4 food treatments - S(tarve), L(ow), M(edium) and H(igh). There are 3 reps of each treatment. I collect data on size of each

Hello all, I have two questions regarding nested anova. I've attached a simple example, where a male is mated with 4 females, and the intensity of the colour of the eyes is measured in two offspring from each female. 1) As I understand it, residuals in a nested anova are the difference between an observed value and the predicted value, which is equal to the sample mean for the cell that

Dear list, I have following data set, which I want to plot the "Scale" variable on the x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean value of each Ageclass for each sex would be connected by a line. Totally, there should be 6 lines, from which three present the Mean values of each Ageclass for respective sex. Are there any easy ways to do

Hi All, I have the data like this : >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

I'm trying to remove the elements "No" from the character vector

Hello R-users/experts, I am new to R- I have a simple question: Let say I have a data set as follows temp:[file attached] the data structure is a follows: sex age female 28 female 53 female 53 female 36 male 42 male 29 male 43 male 36 male 41 Here we are grouping all male value into male and all female value in to female

Hi all, I have data like this: >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

Hi, I have a data set similar to the following State Gender Quantity TX Male 1 NY Female 2 TX Male 3 NY Female 4 I need to calculate cumulative sum of the quantity by State and Gender. The expected output is State Gender Quantity CumQuantity TX Male 1 1 TX Male 3 4 NY Female 2 2 NY Female 4 6 I highly appreciate if someone can give me some hints on solving that in R. Hao -- View this

Hi, I have newbie question. Suppose I have the following data: temp <- data.frame(type1 = c("male", "female", "male", "female", "female"), type2 = c("low", "med", "high", "low", "med"), a = c(1,2,4, NA, 3), b = .... [TRUNCATED] temp type1 type2 a b c 1 male low 1 5 0 2 female

Hey, Is it possible that R can calculate each options under each column and return a summary table? Suppose I have a table like this: Gender Age Rate Female 0-10 Good Male 0-10 Good Female 11-20 Bad Male 11-20 Bad Male >20 N/A I want to have a summary table including the information that how many answers in each category, sth like this: X

I am trying to add confidence (error) bars to lattice barcharts (and dotplots, and xyplots). I found this helpful message from Deepayan Sarkar and based teh code below on it: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/50299.html However, I can't get it to work with groups, as illustrated. I am sure I am missing something elementary, but I am unsure what. Using R 2.1.1 on various

Hello, Say I have 2 columns, bmi and gender, the first being all the values and the second being male or female. How would I subset this into males only and females only? I have searched these fora and read endlessly about select[] and split() functions but to no avail. Also the table is not ordered. bmi gender -> bmi gender + bmi gender 1 24.78 male