I have population size over time with many gaps (the unfortunate reality of many biological data sets!): there are only 12 points over 37 years.
The goal of the analysis is try to figure out what has influenced the population trajectory (climate, human use, predator numbers). My plan was to identify a few candidate models a priori (under competing hypotheses), do several multiple linear regressions, and use AICc to select a model that has the most support. But, I’m leery about using regression with so many gaps in the data, and I’m not sure what is the best response variable under this scenario anyway.
2 questions:
Does regression seem appropriate with the many gaps in the data (most of the independent variables, (i.e. weather, human use) are available for every year!)?
For the DV, I’d like to use a growth rate, to get away from actual “counts” (which would probably require a GLM count-data model), but is it OK to use growth rate if I have up to 15 year gaps in the data?
Any thoughts on this would be appreciated!
The goal of the analysis is try to figure out what has influenced the population trajectory (climate, human use, predator numbers). My plan was to identify a few candidate models a priori (under competing hypotheses), do several multiple linear regressions, and use AICc to select a model that has the most support. But, I’m leery about using regression with so many gaps in the data, and I’m not sure what is the best response variable under this scenario anyway.
2 questions:
Does regression seem appropriate with the many gaps in the data (most of the independent variables, (i.e. weather, human use) are available for every year!)?
For the DV, I’d like to use a growth rate, to get away from actual “counts” (which would probably require a GLM count-data model), but is it OK to use growth rate if I have up to 15 year gaps in the data?
Any thoughts on this would be appreciated!