![]() More specifically, as is common in the literature we analyze the log of the response times, log_rt. ![]() The dependent variable is the response latency or response time for each presented string. length is also a repeated-measures factor that gives the number of characters of the presented strings with three levels: 3, 4, and 5.stimulus is a repeated-measures or within-subjects factor that codes whether a presented string was a word or nonword.task is a between subjects (or independent-samples) factor: 25 participants worked on the lexical decision task ( lexdec i.e., participants had to make a binary decision whether or not the presented string is a word or nonword) and 20 participants on the naming task ( naming i.e., participant had to say the presented string out loud).The data are lexical decision and word naming latencies for 300 words and 300 nonwords from 45 participants. We use data courtesy of Andrew Heathcote and colleagues. Let me illustrate how to calculate an ANOVA with a simple example. On top of this, the ANOVA object returned by afex (of class afex_aov) can be directly used for follow-up or post-hoc tests/contrasts using the lsmeans package. ![]() Together this guarantees that the ANOVA results correspond to the results obtained from commercial statistical packages such as SPSS or SAS. In the default settings, afex automatically uses appropriate orthogonal contrasts for factors, transforms numerical variables into factors, uses so-called Type III sums of squares, and allows for any number of factors including repeated-measures (or within-subjects) factors and mixed/split-plot designs. It provides a set of functions that make calculating ANOVAs easy. I want to use this opportunity to introduce one of the main functionalities of afex. aov_ez did not work with more than one covariate ( thanks to tkerwin for reporting this bug). ![]() This version only fixes a small bug that was introduced in the last version. If you know this feeling, afex is also for you.Ī new version of afex (0.18-0) has been accepted on CRAN a few days ago. After I had gained experience developing my first package and was once again struggling with R and ANOVA I had enough and decided to develop afex. For a newcomer (and even an old timer) this can be somewhat off-putting. Especially for unbalanced designs or designs with repeated-measures replicating the results from such software in base R may require considerable effort. Prelude: When you start with R and try to estimate a standard ANOVA, which is relatively simple in commercial software like SPSS, R kind of sucks. ![]()
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