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2006 Dec 14
3
Model formula question
Hi all,
I'm not familiar with R programming and I'm trying to reproduce a
result from a paper.
Basically, I have a dataset which I would like to model in terms of
successive increments, i.e. (y denote empirical values of y)
y_1 = y1,
y_2 = y1 + delta1,
y_3 = y1 + delta1 + delta2.
...
y_m = y1 + sum_2^m delta j
where delta_j donote successive increments in the y-values, i.e.
delta j = y_j - y_(j-1).
In order to estimate y-values, I'm assuming that delta j is
approximately equal to kj**u, such that my regression model should be
something like this:
^y_1 = a1
^y_2 = a1 + k2**...
2010 Dec 30
1
Different results in glm() probit model using vector vs. two-column matrix response
...p <- r/n
d <- data.frame(group, dose, ldose, n, r, p)
SF <- cbind(success=d$r, failure=d$n - d$r)
#80 record set-up
dose2<-c(7,8,9,10,11)
doserep<-sort(rep(dose2,8))
x<-c(doserep,doserep)
log10x<-log10(x)
y_U<-c(rep(0,8), 1, rep(0, 7), 1, 1, 1, rep(0,5), rep(1, 16))
y_M<-c(rep(0,24), rep(1,4), rep(0,4), rep(1,5), rep(0,3))
y<-c(y_U, y_M)
trt<-c(rep(1, 40), rep(0, 40))
# print x & y's for both
SF
y
ldose
log10x
# analysis with 10 records and 80 records
f1 <- glm(SF ~ group + ldose, family=binomial(link="probit"))
f3 <- glm(SF ~...
2006 Dec 14
0
Model formula
...Hi all,
I'm not familiar with R programming and I'm trying to reproduce a
result from a paper.
Basically, I have a dataset which I would like to model in terms of
successive increments, i.e. (y denote empirical values of y)
y_1 = y1,
y_2 = y1 + delta1,
y_3 = y1 + delta1 + delta2.
...
y_m = y1 + sum_2^m delta j
where delta_j donote successive increments in the y-values, i.e.
delta j = y_j - y_(j-1).
In order to estimate y-values, I'm assuming that delta j is
approximately equal to kj**u, such that my regression model should be
something like this:
^y_1 = a1
^y_2 = a1 + k2**...
2011 May 23
1
help on permutation/randomization test
Hi,
I have two groups of data of different size:
group A: x1, x2, ...., x_n;
group B: y1, y2, ...., y_m; (m is not equal to n)
The two groups are independent but observations within each group are
not independent,
i.e., x1, x2, ..., x_n are not independent; but x's are independent from y's
I wonder if randomization test is still applicable to this case. Does
R have any function that can do...