Chinese fonts

High quality Chinese fonts: http://wqy.sourceforge.net/cgi-bin/index.cgi?%e9%a6%96%e9%a1%b5

Free and open source.

Linux & virus

Interesting post of virus on Linux: http://linuxmafia.com/~rick/faq/index.php?page=virus

Screenshot of my new desktop

Looks pretty cool.

Wow, it's finally here...

A reference manager integrated seamlessly with OpenOffice, on all platforms! Its name is Zotero: http://www.zotero.org/. There is no need to stay with MS-Office just for the convenience of Endnote, and there is no need to stay with Windows just for the combination of Office and Endnote.

It has some very nice features that neither Endnote nor NoteExpress has, such as grab more than one references from google scholars. I realize this is something serious ...

Upgradeing the RGL package on Ubuntu

Remember first to type "sudo apt-get build-dep r-cran-rgl" to get all the necessary files, then do the upgrading.

Ubuntu 7.10 and Stata 10

Ubuntu 7.10 is no doubt the best Linux distro so far. I had some problem installing Stata 10 on my Ubuntu box. When I typed "xstata-se", I got "./xstata: error while loading shared libraries: libtiff.so.3: cannot open shared object file: No such file or directory". Google search pointed me to this url:

http://www.stata.com/support/faqs/unix/libtiff.html

and this:

http://www.stata.com/support/faqs/unix/dynamiclibs.html

Fortunately, the solution is simple: just download the file " tiff-3.7.4.tar.gz", compile and install it, Stata works just fine.

Period effect in Stata

If the time variable is age, how to get Stata to estimate period effect? For a long time, a thought the only way was to use a discrete-time approach: create person-year data format, then estimate either LOGIT or CLOGLOG model. The problem with this approach is: when dealing with large data sets, it becomes impossible to expand the data 10 to 20 times or even more (depends on the duration and the time scale). The only feasible way to get period effect is to use aML's multiple clock capability.

By carefully reading the manual, I realize there is a way to do this. In my schizophenia case, I do the following:

• stset dura_cal, f(event) origin(time birth) id(id)
• stsplit p, at(0, 16, 26) after(time=1949)

Now the STSPLIT command with the "after()" option has correctly splited in data into four segments that represent "before 1949", "1949-1965", "1966-1976", and "after 1976". A simple Cox model can be used to see if the rate of schizophenia is particularly higher in any of the periods:

• xi: stcox i.p

Split-population model (cure model, long-term survivor model)

When there are a portion of respondents who will never experience the event (immortal), ordinary survival modeling techniques are not adequate. Special models designed to handle this kind of situations are called split-population model, cure model, or long-term survivor model.

aML does not handle split-population model; Mplus handles it by imposing constraints on a two-class mixture model; Stata has the following some facilities:

1. lncure: log-normal model with split-population;
2. spsurv: discrete time split-population model;
3. cureregr: split-population model with weibull, lognormal, logistic, gamma, and exponential distribution;
4. strxmix and strsnmix: split-population model with weibull, lognormal, gamma, and some mixture distribution.

Among the above, 1-3 are not well documented, while 4 is described in the most recent issue of Stata Journal (7-3).

For discrete-time models, there are only two alternatives: Mplus or spsurv.

Research on schizophrenia

This article is very interesting:

• St Clair, D., M. Xu, P. Wang, Y. Yu, Y. Fang, F. Zhang, X. Zheng, N. Gu, G. Feng, and P. Sham. 2005. "Rates of Adult Schizophrenia Following Prenatal Exposure to the Chinese Famine of 1959-1961." Journal of American Medical Association 294:557-562.
• http://sciencenow.sciencemag.org/cgi/content/full/2005/802/3
• http://cmbi.bjmu.edu.cn/news/0508/13.htm
  

But my results do not support their findings. Worth some further exploration.