similar to: Identifying records with the correct number of repeated measures

Dear list, I have 9 repeated measures (measurement variable == 'Delta13C') for individuals (ID variable == 'Individual_ID'. Each repeated measure is "indexed" (right term?) by the variable 'FeatherPosition' and given as c('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7', 'P8', 'P9'). I would like to

Dear all, I would like to conduct a Pearson's correlation using cor.test separately for each individual in my data set. Each individual has nine observations of the measurement variable 'Delta13C'. I can figure our how to do it manually one 'Individual_ID' at a time, but I cannot figure out how to automate the process (a loop I am guessing). In addition, I would like to

Dear list, The below dataset and code creates a new dataset with the results from the function cor.test being performed on each individual ('Individual_ID') from my original dataset. How do I convert each variable from the cor.test results to a numeric data type, as it is passed into the new dataframe? For example, 'estimate', 'p.value', and 'conf.int' should be

I have a list of observations of individuals. I would like to make a list of individuals, with a data frame of observations for each individual. The following code usually works, but not always ---------------------------------------------------------------------- # Make a list of empty data frames animals = list() indivs = levels(Z$individual_id) donotprint <- sapply(indivs, function(i){

Hello R users, Doing My PhD I collected count data which I believe is zero inflated. I have run a statistical model with lmer and family=poisson and got summary(model)@sigma=1 so I believe there is no overdispertion. I would like to use the fmr function from the 'gnlm' library but I just cannot figure out from the examples in the help page and some forums out there how to convert the lmer

Hi All, I'm trying to run a simulation of host-pathogen evolution based around individuals. What I need to have is a dataframe or table of some description - describing all the individuals of a pathogen population (so far I've implemented this as a matrix): ID No_of_Effectors Effectors (Sequences) [1,] 0001 3 ## 3

Hi All I am trying to translate a proc mixed into a lme() syntax. It seems that I was able to do it for part of the model, but a few things are still different. It is a 2-level bivariate model (some call it a pseudo-3-level model). PROC MIXED DATA=psdata.bivar COVTEST METHOD = ml; CLASS cluster_ID individual_id variable_id ; MODEL y = Dp Dq / SOLUTION NOINT; RANDOM Dp Dq / SUBJECT = cluster_ID