search for: unbalancing

Hi, I have an unbalanced dataset on which I would like to perform a one-way anova test using R (aov). According to Wannacott and Wannacott (1990) p. 333, one-way anova with unbalanced data is possible with a few modifications in the anova-calculations. The modified anova calculations should take into account different sample sizes and a modified definition of the average. I was wondering if the

Dear list members, I want to use a GLM with an unbalanced factor and continuous variables. My factor F has 12 unbalanced levels:

Hi there, I am looking to fit a two-way random effects model to an *unblalanced* layout, y_ijk = mu + a_i + b_j + eps_ijk, i=1,...,R, j=1,...,C, k=1,...,K_ij. I am interested first of all in estimates for the variance components, sigsq_a, sigsq_b and sigsq_error. In the balanced case, there are simple (MM, MLE) estimates for these; In the unbalanced setup,

I have a three-way unbalanced ANOVA that I need to calculate (fixed effects plus interactions, no random effects). But word has it that aov() is good only for balanced designs. I have seen a number of different recommendations for working with unbalanced designs, but they seem to differ widely (car, nlme, lme4, etc.). So I would like to know what is the best or most usual way to go about working

Dear listserv members, In Croissant (2008) “Panel Data Econometrics in R: The plm Package” the authors seem to indicate that the nlme package for R cannot correctly handle unbalanced panel data: “Moreover, economic panel datasets often happen to be unbalanced (i.e., they have a different number of observations between groups), which case needs some adaptation to the methods and is not

Dear all, I need an help because I am really not able to find over internet a good example in R to analyze an unbalanced table with Anova with repeated measures. For unbalanced table I mean that the questions are not answered all by the same number of subjects. For a balanced case I would use the command aov1 = aov(response ~ stimulus*condition + Error(subject/(stimulus*condition)), data=scrd)

Hello R-users, I am trying to obtain Type III SS for an ANOVA with subsampling. My design is slightly unbalanced with either 3 or 4 subsamples per replicate. The basic aov model would be: fit <- aov(y~x+Error(subsample)) But this gives Type I SS and not Type III. But, using the drop() option: drop1(fit, test="F") I get an error message: "Error in

Hi all, I'm new to R and have the following problem: I have a 2 factor design (a has 2 levels, b has 3 levels). I have an object kidney.aov which is an aov(y ~ a*b), and when I ask for model.tables(kidney.avo, se=T) I get the following message along with the table of effects: Design is unbalanced - use se.contrast() for se's but the design is NOT unbalanced... each fator level

Hello Everyone, *Question: *How do you calculate the sum of squares for a two-way _unbalanced_ ANOVA? *What I have done:* I have found many useful tutorials online for running a balanced two-way ANOVA but I haven't had much luck for running a unbalanced two-way ANOVA. From what I have read, the trouble with running an unbalanced two-way ANOVA, is that things get tricky when calculating

Hi all I'm trying to complete a textbook example originally designed for SPSS in R, and I therefore need to find out how to compute an unbalanced ANOVA in R. I did a search on the mailinglist archives an found a post by Prof. Ripley saying one should use the lme function for (among other things) unbalanced ANOVAs, but I have not been able to use this object. My code gives me an error.. Why

Hello, I'm wondering what's the best way to analyse an unbalanced design with a low number of replicates. I'm not a statistician, and I'm looking for some direction for this problem. I've a 2 factor design: Factor batch with 3 levels, and factor dose within each batch with 5 levels. Dose level 1 in batch one is replicated 4 times, level 3 is replicated only 2 times. all

?s 06:47 de 08/04/2024, Dave Dixon escreveu: > Greetings, > > I have a csv file of 76 fields and about 4 million records. I know that > some of the records have errors - unmatched quotes, specifically. > Reading the file with readLines and parsing the lines with read.csv(text > = ...) is really slow. I know that the first 2459465 records are good. > So I try this: >

I have an unbalanced design I would like to run a power analysis on. What I have been able to find has pointed me to using the pwr.f2.test function as described below. My problem is that I don't know how to appropriately define the numerator and demoninator df. If someone can help here is some more info about my design. It is an unbalanced 2^3 x 3 design where the factor with 3 levels is a

Hello, I was wondering if there was an easy way to calculate the rate of change in a variable for an unbalanced panel data set. Below is a detailed description in R of what I am asking. Thank you. Geoff #Suppose I have the following unbalanced panel data; Person <- c(rep('Frank',5), rep('Tony',4), rep('Edward',4)); Year <-

Greetings from Rio de Janeiro, Brazil. I am looking for advice / references on binary logistic regression with weighted least squares (using lrm & weights), on the following context: 1) unbalanced sample (n0=10000, n1=700); 2) sampling weights used to rebalance the sample (w0=1, w1=14.29); e 3) after modelling, adjust the intercept in order to reflect the expected % of 1?s in the population

Hi all, Say I have the following data: a<-data.frame(col1=c(rep("a",5),rep("b",7)),col2=runif(12)) a_aov<-aov(a$col2~a$col1) summary(aov) Note that there are 5 observations for a and 7 for b, thus is unbalanced. What would be the correct way of doing anova for this set? Thanks, Sachin [[alternative HTML version deleted]]

I am using R for the first time in one of my classes. My students have alerted me to a problem for which we have not found an answer. We find that some means returned by the model.tables function are not correct when missing data is present in analysis of variance problems. We have duplicated the problem using R 1.2.0, 1.2.1, and 1.2.2 under Windows 98 and several distributions of Linux (Redhat

Dear all, I need to do a Manova but I have an unbalanced design. I have morphological measurements similar to the iris dataset, but I don't have the same number of measurements for all species. Does anyone know a procedure to do Manova with this kind of input in R? Thank you very much, Naiara. -------------------------------------------- Naiara S. Pinto Ecology, Evolution and Behavior 1

Hi folks, I have a dataset from a trial measuring the subjects' pupils. There are many measurements, all of which must be analysed in a similar fashion; so if I get the analysis right for one of them, I've got them all. For simplicity, let us call any measurement we may be interested as "response". The study design is an unbalanced latin square, with 5 periods, 5 treatments and

Hi, I have been having some trouble using aov to do an anova, probably because I'm not understanding how to use this function correctly. For some reason it always tells me that "Estimated effects may be unbalanced", though I'm not sure what this means. Is the formula I am using written incorrectly? Below is the code I am using along with the data: > my.data response