Hi
Your choice of package should partly depend on the type of dependent
variable or Y that you are going to be dealing with
categorical/ordinal data may involve different packages than continuous
or binary data see multgee for one.
The number of samples can also make a difference GEE with the "
On 7/12/20 10:42 AM, Tiffany Adekola wrote:
Dear All,
I am just learning how to use R programming. I want to extract reviews
from a page and loop till I extract for all pages:
#specify the first page URL
fpURL <- 'https://wordpress.org/support/plugin/easyrecipe/reviews/'
#read the HTML conte
You may get lucky, but generally such package-specific questions don't get
responses here. There are about 2 packages after all. You might do
better posting on the r-sig-mixed-models list or by asking the package
maintainer (?maintainer) whether there is some sort of support list for the
packag
Hello,
The code below puts the group names as subscripts to 'R'.
The trick is to create each of the labels with those names before
pasting the ..p.label..
This is done by Map, calling a function f defined outside the for loop.
I have also changed your code a bit, simplifying parts of it.
1. I
Dear All,
I am just learning how to use R programming. I want to extract reviews
from a page and loop till I extract for all pages:
#specify the first page URL
fpURL <- 'https://wordpress.org/support/plugin/easyrecipe/reviews/'
#read the HTML contents in the first page URL
contentfpURL <- read_h
Hello,
I have a multi-level, cohort dataset with three levels: repeat measures of a
response (level 1), that are collected from individual participants (level 2)
who are students within a school (level 3). I would like to do a generalized
estimating equation (GEE) analysis of this clustered dat
Thanks a lot - solved the issue!
BW
Troels
-Oprindelig meddelelse-
Fra: Rui Barradas
Sendt: 12. juli 2020 12:59
Til: tr...@gvdnet.dk; r-help mailing list
Emne: Re: [R] Rmpfr correlation
Hello,
Why not write a function COR? Not one as general purpose as stats::cor but a
simple one, t
Hello,
Why not write a function COR? Not one as general purpose as stats::cor
but a simple one, to compute the sample Pearson correlation only.
library(Rmpfr)
COR <- function(x, y){
precBits <- getPrec(x)[1]
n <- mpfr(length(x), precBits = precBits)
x.bar <- mean(x)
y.bar <- mean(y)
Dear friends - I'm calculating buffer capacities by different methods and
need very high precision and package Rmpfr is working beautifully. However,
I have not been able to find out how to keep precision when finding
correlations.
library(Rmpfr)
KA <- mpfr(10^-4.6, 128)
x <- rnorm(100)*KA
y <-
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