search for: demirtas

...al distributions and Pearson correlation as inputs. For example, Y1=(1,2,3) with P(Y1=1)=0.3, P(Y1=2)=0.5, P(Y1=3)=0.2 and Y2=(1,2) with P(Y2=1)=0.6, P(Y2=2)=0.4, and corr(Y1,Y2)=0.5 (Pearson correlation among ordinal variables) How do I calculate the tetrachoric correlation here? Thanks, Hakan Demirtas [[alternative HTML version deleted]]

...diagonals have to be 1 by definition, how do I do it? The above-mentioned function seem to mess up the diagonal entries. [I haven't seen this complication, but obviously all entries must remain in (-1,1) range after conversion.] Any R tools to handle this? I'd appreciate any help. Hakan Demirtas [[alternative HTML version deleted]]

Hi, Is there an R library that has the same functionalities of Splus7.0+ library correlatedData? I'd appreciate any input. Hakan Demirtas [[alternative HTML version deleted]]

Hi, Is there any Fortran compiler that generates R-compatible object files ? (For Windows based systems) Thanks, Hakan Demirtas Pennsylvania State University Department of Statistics [[alternate HTML version deleted]]

Hi, Is there any R library that is capable of handling polygamma function (Hurwitz zeta function also works)? I am aware of digamma(0 and trigamma(), but could not find more advanced versions. I'd appreciate any help. Hakan Demirtas

...her words, we have access to the third and fourth raw moments. How do we solve for these four coefficients? I reduced the number of unknowns/equations to two, and subsequently used a grid approach. It works well when I am close to the center of the support, but fails at the tails. Any ideas? Hakan Demirtas

Does lmer do three-level mixed-effects models? What forms of outcome variables can it handle (continuous, survival, binary)? I'd appreciate any help.

Hi, What R libraries should I use to implement mixed effects models with continuous time and discrete-time survival data? What if I have two crossed random effects? I'd appreciate any help. Regards, Hakan Demirtas [[alternative HTML version deleted]]

I am trying to incorporate random effects (random intercept is good enough) to a proportional odds logistic regression model for ordinal outcomes. Could lme4 do this? I'd appreciate any input. Hakan Demirtas

Hi, Suppose x and y are vectors whose elements are known. I know that there is a sinusoidal relation between them. In other words, y=a*sin(bx) where b is probably a function of pi. How do I find a and b in R? Hakan [[alternative HTML version deleted]]

...org/packages/mets Implementation of various statistical models for multivariate event history data. Including multivariate cumulative incidence models, and bivariate random effects probit models (Liability models) * MultiOrd (1.0) Maintainer: Anup Amatya Author(s): Anup Amatya and Hakan Demirtas License: GPL-2 http://crantastic.org/packages/MultiOrd A method for multivariate ordinal data generation given marginal distributions and correlation based on the methodology proposed by Demirtas (2006). * PEIP (1.2) Maintainer: Jonathan M. Lees Author(s): Jonathan M. Lees License...