Missing data occurs in almost all research, even well-designed and controlled studies. Missing data can reduce power and result in a biased estimate of your effect of interest. In this talk, I will review the mechanisms that give rise to missing data. I will also discuss some of the strategies available to address missingness, such as value substitution and deletion and more advanced methods such as imputation and maximum likelihood.
Speaker: Nancy Briggs, Senior Statistical Consultant and Manager, Stats Central.
The talk will be about 30 minutes long and will be followed by time for discussion. We'll move on after our talk to Hacky Hour (Penny Lane Café, 3.00 pm to 4.00 pm) where people can get help on statistics and bioinformatics, high performance computing and other data-related things.