search for: logitp

...each function has three value as Tr = 1 - 3,how can i combine together? logitTr1 <-logit[logit[,"Study"]&logit[,"Tr"]==1,] (number of row in each group (1-3) is difference but equal in colume) fnTr1 <- function (p) sum( n/2*log(2*pi)+log(1/logitTr1$sd)+1/2*(logitTr1$logitp*logitTr1$logitp-2*logitTr1$logitp*p+p^2) *1/logitTr1$sd*logitTr1$sd ) (maximum likelyhood function) outTr1<- nlm (fnTr1,p=c(10),hessian=TRUE) minimumTr1 <- outTr1$minimum valueTr1 <- outTr1$estimate (estimate the value) The problem is the program couldn't work by...

I was wondering why this loop doesn't work! for (i in 1:k) fnTr[i] <- function (p) 0.5* sum ( n*log(2*pi) - log(sd(i)^2) +(logitp(i)-p)^2/sd(i)^2 ) outTr[i]<- nlm (fnTr[i],p=c(10),hessian=TRUE) minimumTr[i] <- outTr[i]$minimum valueTr[i] <- outTr[i]$estimate list (minimumTr[i],valueTr[i]) Has anyone can help me? Thank you very much Hathaikan

...2) E_ik ~ N(0,s_ik^2) i = number of study k = number of treatment --------------------------------------------------------------------------- I have practiced using the command from 'Mixed -Effects models in S and S-plus' as follow fm1logit.lme <- lme(logitp~1, data=logit, random = ~1|factor(Tr)) It can be written in this model Y_ik = Mew + B_i + E_ik where M_i ~ N(0,sigma_b^2) E_ik ~ N(0,sigma^2) but it is not the same what my model is. Could somebody please point me in the right direction ? Sorry if this turns...

..., -0.3202))3 -11.216 2.861 - 3.920 8.86e-05 *** I think bs(degree=1) has fitted the piecewise linear functions. Now i hope to write the model formua for the above results, but not very sure about how to write the correct results for *distance* and *y,* because they have three parts . Logitp=12.104 + 5.815*x + 6.654*elevation - 6.755*elevation^2 -1.291*distance1 - 10.348*distance2 - 3.53*distance3 -6.828*y1 - 4.426*y2 - 11.216*y3 In the above formula, distance1-3 denotes the three linear functions for*distance *, my problem is how to replace distace1-3 using origi...