Dear R-experts,
The forest.rma() function from the metafor package creates nice forest
plots for presenting the results of a meta-analysis. These plots can be
annotated for e.g. giving names to the columns. E.g. as in the
documentation of the package:
data(dat.bcg)
### meta-analysis of the log r
Dear R experts,
I have conducted a power calculation in order to estimate the number of
subjects needed to detect an effect size of d=0.28 (cohen's d) for a
difference between two independent groups (alpha level should be 0.05 and
the effect should be detected with 80% probability).
The results fr
Dear R-experts!
I having trouble with the correct implementation of a mixed-model ANOVA in
R.
I my dataset subjects were tested in a cognitive performance test
(numerical outcome variable 'score'). This cognitive performance test is
devided into five blocks (categorical factor 'block'). All subj
Dear R communitiy,
I am trying to use multiple functions for aggregation within a function
call for dcast. However this seems to result in an error. Also I have not
managed to make dcast() work with fun.aggregate=sd. Please find attached
some example code using the ChickWeight data.
Many thanks f
Dear R-List!
I would like to embed R code in an online database such as i.e. a google
spreadsheet in way that users can add data to the database and that R's
calculations are updated automatically and i.e. given out in the
spreadsheet. Maybe even graphs could be updated online? Is there a way to
i
Dear R-list!
I am using the e1071 package in R to solve a binary classification problem
in a dataset of round 180 predictor variables (blood metabolites) of two
groups of subjects (patients and healthy controls). I am confused regarding
the correct way to assess the classification accuracy of the t
Dear R-Users!
I am using the svm function (e1071 package) to classify two groups using a
set of 180 indicator variables. Now I am confused about the cross-validation
procedure.
(A) On one hand I use the setting cross=10 in the svm function to run 10
cross-validation iterations and to get an estim
Dear R-experts!
In a meta-analysis (metafor) I would like to assess the effect of two
categorical covariates (A & B) whereas they both have 4 levels.
Is my understanding correct that this would require to dummy-code (0,1) each
level of each covariate (A & B)?
However I am interested in the main-ef
Dear R-experts!
I found a great post on the "getting genetics done" blog which describes how
to make use of NCBI E-utilities in Python to extract data from PubMed:
http://gettinggeneticsdone.blogspot.com/2011/05/using-ncbi-e-utilities.html
I was wondering whether there would be a way to directly
Dear R-experts!
Running a meta-analysis (using the magnificent metafor-package), I use
cohen's d as a main outcome measure in a random-effects model.
For most of the samples cohen's d is derived form a comparison of two groups
(A & B). However some studies report results from an ANOVA (one-factor
Dear R-experts!
I am working on some meta-analysis using the metafor package. I would like
to extract values of the confidence intervals of the effect sizes of the
single studies from an rma object. Those values are printed out when
plotting a forest plot using the forest function on the rma objec
Dear R-experts!
I am currently running a meta-analysis with the help of the great metafor
package. However I have some difficulties setting up my raw data to enter it
to the meta-analysis models.
I have a group of subjects that have been measured in two continuous
variables (A & B). I have the inf
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