search for: dadrivr

so I am trying to get my R setup to run this users package. Any help would be great THANKS devtools::install_github(repo = "dadrivr/ffanalytics") I get this devtools::install_github(repo = "dadrivr/ffanalytics") Downloading GitHub repo dadrivr/ffanalytics at master from URL https://api.github.com/repos/dadrivr/ffanalytics/zipball/master Installing ffanalytics "C:/PROGRA~1/R/R-33~1.3/bin/x64/R" --no-si...

...sting Guide. -- Sent from my phone. Please excuse my brevity. On August 18, 2017 7:33:35 AM PDT, Zack Haney <zack.haney at gmail.com> wrote: >so I am trying to get my R setup to run this users package. Any help >would >be great THANKS > >devtools::install_github(repo = "dadrivr/ffanalytics") > >I get this > >devtools::install_github(repo = "dadrivr/ffanalytics") >Downloading GitHub repo dadrivr/ffanalytics at master >from URL >https://api.github.com/repos/dadrivr/ffanalytics/zipball/master >Installing ffanalytics >"C:/PROGRA~...

...y phone. Please excuse my brevity. > > On August 18, 2017 7:33:35 AM PDT, Zack Haney <zack.haney at gmail.com> wrote: >>so I am trying to get my R setup to run this users package. Any help >>would >>be great THANKS >> >>devtools::install_github(repo = "dadrivr/ffanalytics") >> >>I get this >> >>devtools::install_github(repo = "dadrivr/ffanalytics") >>Downloading GitHub repo dadrivr/ffanalytics at master >>from URL >>https://api.github.com/repos/dadrivr/ffanalytics/zipball/master >>Installing...

Is it possible to change the color/thickness of the summary line in an interaction.plot without changing the other individual data lines? I would like to make the line from the summary function (mean) the color red and thicker than the surrounding black lines. How can I do that? Here is a link to interaction.plot: http://stat.ethz.ch/R-manual/R-patched/library/stats/html/interaction.plot.html

Hi everyone, I am trying to make some publication-quality plots for use in Microsoft Word, but I am having trouble creating high-quality plots that are supported by Microsoft Word. If I use the R plot function to create the figure, the lines are jagged, and the picture is not of high quality (same with JPEG(), TIFF(), and PNG() functions). I have tried using the Cairo package, but it distorts

I am trying to reshape a data set. Could someone please help me with the reshape, cast, and melt functions? I am new to R and I have tried reading up on how to use the reshape package, but I am very confused. Here is an example of what I am trying to do: subject coder score time [1,] 1 1 20 5 [2,] 1 2 30 4 [3,] 2 3 10 10 [4,] 2 2

I am trying to plot an interaction in a multilevel model. Here is some sample data. In the following example, it is longitudinal (i.e., repeated measures), so the outcome, score (at each of the three time points), is nested within the individual. I am interested in the interaction between gender and happiness predicting score. id <- c(1,1,1,2,2,2,3,3,3) age <-

I'm trying to write code to calculate partial correlations (along with p-values). I'm new to R, and I don't know how to do this. I have searched and come across different functions, but I haven't been able to get any of them to work (for example, pcor and pcor.test from the ggm package). In the following example, I am trying to compute the correlation between x and y, while

How do I subset data to only keep those rows of a dataframe where a variable's value matches one item of a vector. For example, how do I keep all of the rows (and all variables) where mydata$id equals one of the values in keepid? See below? mydata <- NULL mydata$id <- 1:30 mydata$value <- seq(from=1,to=100, length.out=30) keepid <- c(6,10,12,13,19,25,26,27,28,29) In other

I would like to preface this by saying that I am new to R, so I would ask that you be patient and thorough, so that I'm not completely clueless. I am trying to convert a list to numeric so that I can perform computations on it (specifically mean-center the variable), but I am running into problems. I have imported the data set into "task" (data frame). The data frame is made of

Hi all, I am trying to plot the fitted trajectories for each individual from an individual growth model (fit with a linear mixed effects model in lme). How can I plot each person's trajectory in the *same* panel, along with the mean-level trajectory? Below is an image of a plot similar to what I'm trying to create (from: http://jpepsy.oxfordjournals.org/content/31/10/1002/F6.large.jpg):

Hi, I'm trying to reshape my data set from wide to tall format for multilevel modeling. Unfortunately, the function I typically use (make.univ from the multilevel package) does not appear to work with unbalanced data frames, which is what I'm dealing with. Below is an example of the columns of a data frame similar to what I'm working with: ID a1 a2 a4 b2 b3 b4 b5 b6 Below

I'm trying to make correlograms using corrgram. See below for a simple example. #### library(corrgram) data(baseball) vars1 <- c("Assists","Atbat","Errors","Hits","Homer","logSal") vars2 <- c("Putouts","RBI","Runs","Walks","Years")

I am fitting individual growth models using nlme (multilevel models with repeated measurements nested within the individual), and I am trying to calculate the Pseudo R-squared for the models (an overall summary of the total outcome variability explained). Singer and Willett (2003) recommend calculating Pseudo R-squared in multilevel modeling by squaring the sample correlation between observed and

Hi, I have a string that I want to use in a variable call. How can I remove the quotes and/or the string properties of the string to use it in a variable call? Here's an example: library(lme) fm2 <- lme(distance ~ age, data = Orthodont, random = ~ 1) summary(fm2) I want to update the above regression to include new predictors according to what is in a string: predictors <-

I'm trying to treat a continuous variable as discrete for plotting multiple regression lines in a scatterplot as a function of the level on the moderating variable. In the example below, there is only one regression line plotted to the whole data. I would like a separate regression line for each discrete level of the moderator. The moderator is continuous, so I'd like to treat it as

I'm fitting a lme growth curve model with two predictors and their interaction as predictors. The multilevel model is nested so that level 1 is time within the individual, and level 2 is the individual. I would like to plot the mean group-level trajectories at plus and minus 1 SD from the mean of the main effects composing the interaction term. Thus, the plot should have 4 lines (mean

Hi, I am trying to apply the example at the bottom of the following page to my own data: http://128.97.141.26/stat/R/faq/spagplot.htm http://128.97.141.26/stat/R/faq/spagplot.htm The code from the example is: /tolerance<-read.table("http://www.ats.ucla.edu/stat/R/faq/tolpp.csv",sep=",", header=T) fit <- by(tolerance, tolerance$id,function(x) fitted.values(lm(tolerance

I am using a multilevel modeling approach to model change in a person's symptom score over time (i.e., longitudinal individual growth models). I have been using the lme function in the multilevel package for the analyses, but my problem is that my outcome (symptoms) and one of my predictors (events) are count data, and are non-normal. Do you have any suggestions for how to deal with them?

Hi, I want to impute a data set multiple times with Amelia, but the data set is large so it takes a long time. As a result, I'm trying to run the multiple imputation with parallel processors in Windows, but am having trouble. Here is a quick example: ###### library(foreach) library(doSNOW) registerDoSNOW(makeCluster(4, type = "SOCK")) getDoParWorkers() getDoParName()