Dear list, This is NOT a techical question ragrding use of R.
I have a linear model where the response variable is neigborhood safety . It is projected poverty deteriorate safety and number of officers per thousand residents improve safety. The focal hypothesis is poverty poses less safety threat when officers number is high. To check the focal hypothesis, the continuous variable "officers" is recoded as catogorical with two levels (high and low). the results is below and support the hyothesis #========================================= model <- lm(neigborhood safety ~ poverty * officers) The coefficients (all significant): poverty -0.05 officers 0.058 poverty : officers 0.014 #========================================== My question is how to check the weakened "poverty" effect with a minuscle increase of "officers". the coeeficient for the interaction term of continous "poverty" and "officers" is hard to interpret and is not suitable to check the focal hypothesis since, say, (povety=3 & officers=8) will be the same as (poverty=8 & officer=3). Thanks a lot in advance for any suggestions! Sincerely, Will ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
