Positive continuous outcome; PROC GENMOD DATA=dat; MODEL cost = age sex / DIST=GAMMA LINK=LOG; RUN;
The concept of GenMod dates back to the 1970s, when scientists first discovered ways to manipulate DNA in a laboratory. However, it wasn't until the 1990s that genetic modification became a mainstream field, with the development of genetically modified crops (GMCs) that could resist pests and diseases. genmod
: Unlike simple least-squares regression, GenMod uses MLE to estimate parameters, ensuring the most likely coefficients are found based on the observed data. Practical Applications of GenMod Positive continuous outcome
: Strictly for normal distributions (standard linear regression). PROC GENMOD DATA=dat
What are you analyzing? (Counts, Binary, Continuous?) Is it repeated measures (same subjects over time)?