search for: geriatrics

??I would like to apply a function, fract, to the columns of a dataframe. I tried the following apply(data5NonEventEpochs,2,fract) but, no surprise it did not work as apply works on matrices not data frames. How can I apply a fuction to the columns of a data frame? (I can't covert data5NonEventsEpochs to a matrix as it contains character data). Thank you, John John David Sorkin M.D., Ph.D.

Hello, I want to find the roots of an equation in two variables. I am aware of the uniroot function, which can do this for a function with a single variable (as I understand it...) but cannot find a function that does this for an equation with more than one variable. I am looking for something implementing similar to a Newton-Raphson algorithm. Thanks. -- Bill Shipley North American Editor for

Hi, I am running a simulation study with the survival::coxph. Some of the simulations result in problematic fits due to flat partial likelihood. So, you get the warning message: Warning message: In fitter(X, Y, strats, offset, init, control, weights = weights, ... : Loglik converged before variable 2 ; beta may be infinite. How can I keep track of the simulations which yield any kind of

Hi! I need to conditionally update a dataframe field based on values in other fields and can't find even how to search for this right. Sorry if this has been asked before. But, specifically, I have a 490 X 221 dataframe and need to count, by row, how many fields in Dataframe$field_a...Dataframe$field_zz are non-null and enter this value in Dataset$ABCtaskNum. I have field name

Hi, I have a right-censored (positive) random variable (e.g. failure times subject to right censoring) that is observed for N subjects: Y_i, I = 1, 2, ..., N. Note that Y_i = min(T_i, C_i), where T_i is the true failure time and C_i is the censored time. Let us assume that C_i is independent of T_i. Now, I would like to generate another random variable U_i, I = 1, 2, ..., N, which is

Hi, I would like to know how to capture the console output from running an algorithm for further analysis. I can capture this using capture.output() but that yields a character vector. I would like to extract the actual numeric values. Here is an example of what I am trying to do. fr <- function(x) { ## Rosenbrock Banana function on.exit(print(f)) x1 <- x[1] x2 <- x[2]

Hi, I would like to solve a system of coupled ordinary differential equations, where there is a delay (time lag) term. I would like to use the "lsoda" function "odesolve" package. However, I am not sure how to specify the delay term using the syntax allowed by odesolve. Here is an example of the kind of problem that I am trying to solve: > library(odesolve)

...s "2020-09-17_00:00:00" How can I convert the elements into a valid R date-time constant? Thank you, John John David Sorkin M.D., Ph.D. Professor of Medicine, University of Maryland School of Medicine; Associate Director for Biostatistics and Informatics, Baltimore VA Medical Center Geriatrics Research, Education, and Clinical Center;? PI?Biostatistics and Informatics Core, University of Maryland School of Medicine Claude D. Pepper Older Americans Independence Center; Senior Statistician University of Maryland Center for Vascular Research; Division of Gerontology and Paliative Care, 1...

How would one generate data to be used in a simulation of a repeated measures ANOVA given a known (1) within-person correlation with known (2) mean and SD of data obtained at each of three times of observation? Thanks, John John Sorkin Chief Biostatistics and Informatics Univ. of Maryland School of Medicine Division of Gerontology and Geriatric Medicine JSorkin at grecc.umaryland.edu

Hi, I would like to know whether there exist algorithms to compute the coefficients or, at least, the degree of the minimal polynomial of a square matrix A (over the field of complex numbers)? I don't know whether this would require symbolic computation. If not, has any of the algorithms been implemented in R? Thanks very much, Ravi. P.S. Just for the sake of completeness, a

Windows 10 64-bit, R-Studio, R version 3.4.3 Several questions relating to groupedData: (1) I am trying to create a groupedData object that can be used to run an analysis that I have been able to urn using lmer. When I include the interaction terms in the groupedData opbject I get an error message stating that + is not meaningful for factors. How do I include factors in my model? See code and

David, predict.glm and se.fit were exactly what I was looking for. Many thanks! John John David Sorkin M.D., Ph.D. Professor of Medicine Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 (Phone) 410-605-7119 (Fax)

Hi, I apologize for the previous posting, where the message was not formatted properly. Here is a better version: I have written the following function to check whether a vector has elements satisfying monotonicity. is.monotone <- function(vec, increase=T){ ans <- TRUE vec.nomis <- vec[!is.na(vec)] if (increase & any(diff(vec.nomis,1) < 0, na.rm=T)) ans <- FALSE

Dear R group, I have a data frame which contains data on preferences on 7 items (ranks 1 through 7) listed by each participant. I would like to tabulate this in a 7x7 table where the rows would be the items and the columns would be the number of times that item received a particular rank. I tried doing this by creating a matrix by "rbind"ing each vector obtained using

David, Again you have my thanks!. You are correct. What I want is not technically a contrast. What I want is the estimate for "regional" and its SE. I don't mind if I get these on the log scale; I can get the anti-log. Can you suggest how I can get the point estimate and its SE for "regional"? The predict function will give the point estimate, but not (to my knowledge)

Dear UseRs!, Everything about UseR! 2010 was terrific! I really mean "everything" - the tutorials, invited talks, kaleidoscope sessions, focus sessions, breakfast, snacks, lunch, conference dinner, shuttle services, and the participants. The organization was fabulous. NIST were gracious hosts, and provided top notch facilities. The rousing speech by Antonio Possolo, who is the chief

Hi, I have a simple problem that I would appreciate getting some tips. I am using the "truehist" function within an "apply" call to plot multiple histograms. I can't figure out how to get truehist to use the column names of the matrix as the labels for the x-axis of the histograms. Here is a simple example: X <- matrix(runif(4000),ncol=4) colnames(X)

Windows 7 (local computer) Windows server (server I am trying to reach) I need to read a file whose windows path is of the form \\Theserver\mydirectory\data.csv You will note that as per windows standards the server name is preceded by two backslashes. I am not sure how to specify this in R. One usually needs to specify an escape characters in a path new which would suggest my path should

If this is posted elsewhere I cannot find it. I need to perform multiple integration where some of the variables are in the bounds of the other variables. I was trying to use R2Cuba function but cannot set the upper and lower bounds. My code so far is : int <- function(y){ u2 = y[1] z2 = y[2] u1 =y[3] z1 = y[4] ff <- u1*(z1-u1)*u2*(z2-u2)*exp(-0.027*(12-z2)) return(ff) }

I am trying to get the mean of a row of a data frame. My code follows: roop <- data.frame(x=c(1,2,3),y=c(4,5,2),z=c(0,9,4)) roop mean(roop[1,]) mean(roop[1,c("x","y","z")]) I get the following output: > roop x y z 1 1 4 0 2 2 5 9 3 3 2 4 > mean(roop[1,]) [1] NA Warning message: In mean.default(roop[1, ]) : argument is not numeric or logical: