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Hello, duplicated() does not seem to work for a long vector. For example, if you download the data from https://docs.google.com/open?id=0B6-m45Jvl3ZmNmpaSlJWMXo5bmc (a vector with about 12,000 numbers) and then run the following code which does duplicated() over the whole vector but just shows the last 30 elements: data.frame( tail(verylong, 30), tail(duplicated(verylong), 30) ) you'll see

Hello everyone, Does anyone know what would cause the skewness() function (from e1071), as well as skew() from psych, to return a value of NaN? I have a vector of positively-skewed data (https://docs.google.com/file/d/0B6-m45Jvl3ZmYzlHRVRHRURzbVk/edit?usp=sharing) which these functions return a value for like normal: > skewness( data ) # returns 1.400405 but when I instead give those

Hello everyone, I've conducted a Type III repeated-measures ANOVA using Anova() from the car package, based on the suggestions at http://blog.gribblelab.org/2009/03/09/repeated-measures-anova-using-r/(option 3) and http://languagescience.umd.edu/wiki/EEG#ERP_ANOVA_in_R. My ANOVA has two factors: Condition (3 levels) and Region (6 levels) and their interaction. Below is code to run the Anova

Hello everyone, I am running a mixed effects model where I have two fixed factors, one with 2 levels and one with 4, and their interaction. Let's say these are my factors and their levels: FirstFactor: 1, 2 SecondFactor: A, B, C, D For the interaction, I am interested in the four two-way comparisons, not the two four-way comparisons. In other words, I want to test whether 1A is

Hello, I have a list of data with multiple elements, and each element in the list has multiple variables in it. Here's an example: ### Make the fake data dv <- c(1,3,4,2,2,3,2,5,6,3,4,4,3,5,6) subject <- factor(c("s1","s1","s1","s2","s2","s2","s3","s3","s3",

Hello Amelie, I don't have an answer to your question, but I just wanted to point out this page I noticed recently ( http://hlplab.wordpress.com/2009/05/07/multinomial-random-effects-models-in-r/), which might be helpful. I'm also interested in figuring out how to do a multinomial glmm, so if you find out anything I'd be happy to hear more about it! Based on what I've found so

Hello everyone, I am testing a model in which I have a two-level factor (let's call it First [1, 2]) nested under a four-level factor (let's call it Second [A, B, C, D]). I have used the following model to get coefficients representing whether, for each level of Second, there is a significant difference (in the outcome variable, Latency) between the levels of First: test <- lmer(