Mountain goats (Oreamnos americanus) in coastal British Columbia and Alaska use lower elevation forests during winter relative to other seasons. Although conventional radiotelemetry is one potential method for studying coastal goats, signal reflection, reliance on clear weather for relocations, and potential harassment of goats during critical winter or kidding periods, all present shortcomings. Global Positioning System (GPS) wildlife collars offer a potential solution to these problems, yet introduce other problems. Some of the most challenging environments for acquisition of GPS fixes, namely incised, heavily forested valleys, are typical within coastal goat habitat. Even in less demanding environments, observation bias exists. Although habitat researchers are aware of this bias, the problem may be underestimated within particular environments. I collared 4 mountain goats within the Stafford River Valley on the mainland coast of B. C. to test GPS wildlife collar performance in challenging terrain and to examine the consequences of GPS observation bias for habitat-selection studies. I also tested the repeated fix success of similar collars placed at sites that differed in forest canopy and topographical relief. After leaving these stationary collars to attempt fix locations over a 24-h period, I determined the percentages of fixes in 2D, 3D and unsuccessful fix classes. I combined digital elevation models with a Geographic Information System (GIS) script to quantify available windows of satellite "sky" that were accessible from each test location. This "window" index, combined with surveyed and digitised habitat variables, allowed me to parameterise multiple regression equations that successfully predict the likelihood of receiving a GPS fix of various fix classes at a given location. From these ground truthing equations and spatially-explicit GIS projections of fix likelihood, I determined the likelihood of obtaining a GPS fix within any portion of the Stafford River study area. I was therefore able to match each individual goat's locations directly to a GPS fix probability. A significant correlation between mean predicted fix likelihood and observed seasonal fix success of collared animals was observed. I then applied a simple and conservative correction factor to each fix location before conducting a habitat selection analysis. Analyses of corrected and uncorrected data show that the consequence of failing to correct 3D data for observation bias can be severe. My analyses of uncorrected data indicate significant selectivity for habitats that differ from those which mountain goats are actually selecting.