search for: unbalanc

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 sa...

Dear list members, I want to use a GLM with an unbalanced factor and continuous variables. My factor F has 12 unbalanced levels: F=as.factor(c('A','B','C','C','C','C','D','D','D','D','D','D','E','E','E','E','E','E...

...d* 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, this is much more complicated because orthogonality relations no longer exist between "row space" and "column space". Since the covariance structure between the cell means y_{ij.} is much more complicated than in the one-way (unbalanced) case, trying to manually obtain...

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 wo...

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 compatible with those in nlme” (pg. 2, Croissant 2008). However in Pinhiero and Bates (2000...

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) Does the same c...

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 UseMethod("extractAIC") : no...

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 combination has the same n I' d appreciate any help. Thanks.

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 calcul...

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 is that ? > aov(lme(DELAY ~ DOSE + TRIALS,dat...

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 repli...

...self-contained, reproducible code. Hello, Can the following function be of help? After reading the data setting argument quote=FALSE, call a function applying gregexpr to its character columns, then transforming the output in a two column data.frame with columns Col - the column processed; Unbalanced - the rows with unbalanced double quotes. I am assuming the quotes are double quotes. It shouldn't be difficult to adapt it to other cas, single quotes, both cases. unbalanced_dquotes <- function(x) { char_cols <- sapply(x, is.character) |> which() lapply(char_cols, \(i)...

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...

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 <- c(2005,2006,2007,2008,2009,2005,2006,2008,2009,20...

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 (e.g., circa 7%, as opposed to 50%). I have identified references that deal with the last point, bu...

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]]

you say you asked elsewhere, but so many hits come up when I just search for "unbalanced sample size" your justification for not following the posting guide does not seem honest. I also recall that various discussions of statistical power address this in basic statistics. On August 24, 2024 11:05:12 AM PDT, Christofer Bogaso <bogaso.christofer at gmail.com> wrote: >H...

...15.333 trtmnts 1 2 3 10.50 13.75 19.00 Entering the data again and dropping treatment 2, block3 and treatment 3, block 4, we have: > blocks2<-factor(c(1,2,3,4,1,2,4,1,2,3)) > trtmts2<-factor(c(1,1,1,1,2,2,2,3,3,3,)) > data2<-c(10,12,9,11,13,15,16,18,22,17) > unbalanced<-aov(data2~blocks2+trtmts2) > summary(unbalanced) Df Sum Sq Mean Sq F value Pr(>F) blocks2 3 18.267 6.089 7.4341 0.0410993 * trtmts2 2 126.557 63.279 77.2587 0.0006367 *** Residuals 4 3.276 0.819 --- Signif. codes: 0 `***' 0.001 `**' 0.0...

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...

...easuring 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 6 subjects. Each subject has two measurements: left and right eyes. The model is as follows, with ":" denoting interaction... Fixed Effects = (Subject + Period + Dose):Eye Random Effects = Subject:Period + Subject:Period:Eye My main quest...