¹Institute for Medical Statistics & Genetic Epidemiology, University of Bonn, Bonn, Germany

²Department of Human Genetics, University of California at Los Angeles, Los Angeles, California, USA

³Department of Biostatistics, University of California at Los Angeles, Los Angeles, California, USA

⁴Program for Population Genetics, Harvard School of Public Health, Boston, Masachusetts, USA

⁵Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA

Correspondence to: S Horvath, UCLA Department of Human Genetics, Gonda Neuroscience & Genetics Research Center, 695 Charles E Young Dr. South, Suite 6506, Los Angeles, CA 90095-7088, USA. Tel: +1 310 825 9299; Fax: +1 810 277 7453; E-mail: shorvath@mednet.ucla.edu

With possibly incomplete nuclear families, the family based association test (FBAT) method allows one to evaluate any test statistic that can be expressed as the sum of products (covariance) between an arbitrary function of an offspring's genotype with an arbitrary function of the offspring's phenotype. We derive expressions needed to calculate the mean and variance of these test statistics under the null hypothesis of no linkage. To give some guidance on using the FBAT method, we present three simple data analysis strategies for different phenotypes: dichotomous (affection status), quantitative and censored (eg, the age of onset). We illustrate the approach by applying it to candidate gene data of the NIMH Alzheimer Disease Initiative. We show that the RC-TDT is equivalent to a special case of the FBAT method. This result allows us to generalise the RC-TDT to dominant, recessive and multi-allelic marker codings. Simulations compare the resulting FBAT tests to the RC-TDT and the S-TDT. The FBAT software is freely available. European Journal of Human Genetics (2001) 9, 301-306.

TDT; RC-TDT; linkage disequilibrium; missing genotypes; censored traits; FBAT