[R] Differences between SPSS and R on probit analysis
tedwin183 at comcast.net
Thu Jun 22 18:55:14 CEST 2017
I hope you’ve solved your problem with SPSS and R probit analysis, but if you haven’t, I have your solution:
Based on the output you’ve given, I see that your residual deviance is under-dispersed (that the ratio of residual deviance to residual deviance df does is less than 1). However, you’ve told R to treat your dispersion parameter as 1 (you did this by using the ‘family = binomial’ argument). Instead, if you use ‘family=quasibinomial’ you allow the dispersion parameter to be estimated. This changes how the variance, SE, etc are calculated. Modeling it this way is akin to the SPSS method, and thus produces nearly-identical results. You may still see very, very minor differences in chi square goodness of fit, and 95% CI of the doses/concentrations, etc. but this is due to differences in rounding under the hood of the software.
Hope this helps!
Edwin R. Burgess IV, Ph.D.
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