similar to: plotting missing data patterns

Dear R-Users, I have a trivial problem, but extensive googling and ??'ing did not solve it: I want to obtain the sums of squares from a summary.aov() object for later use. Example: > DV <- rnorm(100) > IV1 <- as.factor(rep(c("male", "female"), times = 50)) > IV2 <- as.factor(rep(c("young", "old"), times = 50)) > >

Dear all, I try to conduct a SEM / two stage least squares regression with the following equations: First: X ~ IV1 + IV2 * Y Second: Y ~ a + b X therein, IV1 and IV2 are the two instruments I would like to use. the structure I would like to maintain as the model is derived from economic theory. My problem here is that I have trouble solving the equations to get the reduced form so I can run

I have data from a design in which items are completely nested within subjects. Subject is the only second-level factor, but I have multiple first-level factors (IVs). Say there are 2 such independent variables that I am interested in. What is the proper syntax to fit a mixed-effects model with a by-subject random intercept, and by-subject random slopes for both the 2 IVs? I can

Hi all, I have data from an experiment with 3 independent variables, 2 are within and 1 is between. In addition to the dependent variable, I have a covariate that is a single measure per subject. Below I provide an example generated data set and my approach to implementing the ANCOVA. However the output confuses me; why does the covariate only appear in the first strata? Presumably it should

Hello everyone, I have tried to look for this everywhere and so far have no luck. I have a plotMeans(DV, IV1, IV2, error.bars="se") graph that plots my data (DV-continuous, IVs are factors, IV1 - two levels, IV2-four levels). I am trying to increase a scale of my y-axis (to be consistent with my other graphs), but unfortunately nothing works with "plotMeans" function, which

While rototilling packet.c, I did some looking at cipher_encrypt in cipher.c. It ends up that for SSH_CIPHER_NONE in cipher_encrypt, it uses memcpy. However, it also appears that dest and src can be equal in cipher_encrypt. On most sane libc implementations, memcpy == memmove. However, ANSI C makes no such guarantee, and some implementations out there are bound to try to optimize memcpy

Hello, I was hoping for some advice to resolve a problem I am having trouble with. The data consists of a series of pre and post variables, in a dataframe called 'offend'. I am interested in graphically depicting the pre & post values for a factor variable called 'decision' which has 4 values : nusm, fit, unsound & unfit. An example of a pre and post variable is:

Hi all, I have been struggling with ANOVAs on R. I am new to R, so I created a simple data frame, and I do some analyses on R just to learn R and then check them on SPSS to make sure that I am doing fine. Here is the problem that I've run into: when we use the aov function, it uses SS Type I as default (on SPSS it is Type III). Then I used the Anova function under cars package using the

Does anyone know if there is a way to run multivariate linear regression in R? I tried using the lm function (e.g., lm(dv1, dv2~iv1+iv2+iv3), but got error messages. Is my syntax wrong, or do I need a particular package? Thanks, Jeff-- ________________________________________________________ Jeffrey J. Lusk, Ph.D. Postdoctoral Research Associate Department of Forestry &

# I've tried to make this easy to paste into R, though it's probably so simple you won't need to. # I have some data (there are many more variables, but this is a reasonable approximation of it) # here's a fabricated data frame that is similar in form to mine: my.df <- data.frame(replicate(10, round(rnorm(100, mean=3.5, sd=1)))) var.list <- c("dv1",

Dear R users,    my question concerns my interest in comparing the beta coefficients between two identical regression models in two (actually 3) groups. Disclaimer: I am quite new to R, so I might be missing some terminology that I have not come across.   I am trying to find out if I can easily implement a Wald test in R for this, but the only relevant thing that I came across is this link

Hello! I have data containing a large number of probabilities (about 60) of nonzero coefficients to predict 10 different independent variables (in 10 different BMA models). i've arranged these probabilities in a matrix like so: (IV1) (IV2) (IV3) ... p(b0) p(b0) p(b0) p(b1) p(b1) p(b1) p(b2) p(b2) p(b2) ... where p(b1) for independent variable 1 is p(b1 !=

On Apr 18, 2010, at 11:08 PM, John Criswell wrote: > Second, why are you only interested in user time? The reason why we had > RunSafely.sh measure user + system time is that it gives a more accurate > depiction of how well an optimization works. If a program spends most > of its time in the OS, increasing speed in user-space doesn't gain us > much. If a transform

List, I have looked through several R books and searched the web to find answers to my questions with no results. I have a ensembles of time series data (essentially from Monte Carlo simulations) which I would like to summarize as a time series of boxplots. I don't know how to do this and I am not sure how I should structure the data to get what I want. Another related question: while

Hi, Can someone interpret how HVM guest communicate with domain0, as i know, H VM can not use event channel directly, is the platform-pci offer a way to solve this? Please try to explain concretely, for example : 1.how does HVM send a event to domain0, how does domain0 catch this event, and assoicate it with a handler 2.the opposite direction, how does domain0 send event to HVM guest? Does it

Hallo there, I've got a simple question concerning a plot attempt of mine. I am trying to plot two variables using the following code: # Creating a Graph attach(Jitirana) plot(Sozialkapital, Migration) abline(lm(Migration~Sozialkapital)) title("Regression of Sozialkapital on Migration") Simple thing, but the problem lies in the fact that I keep receiving a square plot depicting y on

Hola erreros. A ver si alguien podría decirme qué son los dos ejes del plot que resulta de aplicar partialPlot en un Randomforest. Encuentro que: Partial dependence plot gives a graphical depiction of the marginal effect of a variable on the class probability (classification) or response (regression) que nos indica como varía la VR en función de la variable considerada, manteniendo el

Dear R helpers, I have a data set with 4 types (W, C, E & S). Now I have values for all types plus all possible combinations (the order is unimportant): W, C, WC, E, WE, CE, WCE, S, WS, CS, WCS, ES, WES, CES & WCES. Ideally I would like to represent everything in one graph and as concise as possible. Drawing 4 circles and depicting it as overlap just gives me 13 out of the 15

Hi, I would like to simulate data with a binary outcome and a set of predictors that are correlated. I want to be able to fix the number of event (Y=1) vs. non-event (Y=0). Thus, I fix this and then simulate the predictors. I have 2 questions: 1. When the predictors are continuous, I can use mvrnorm(). However, if I have continuous, ordinal and binary predictors, I'm not sure how to simulate

Greetings; I've been reading the OpenSSH source code and have a question about the des_ssh1_setiv function in cipher.c. (cut-n-pasted here from cipher.c v1.47) : static void des_ssh1_setiv(CipherContext *cc, const u_char *iv, u_int ivlen) { memset(cc->u.des.iv, 0, sizeof(cc->u.des.iv)); } This doesn't use the *iv parameter. Compare with: static void