Ordered multinomial categories or negative binomial

[daoudasissoko]

Hello everbody,
I'm working on vaccine doses received by under-5 children. Precisely, each children may receive either one, two or three doses of this vaccine (DTP-1, 2 and 3 report cumulative numbers -children who received 3 doses are included in dose 2 which are also included in dose 1). Initially, I considered this outcome as a count which distribution displays a non equivalence/ variance. Then, I fitted four-level negative binomial ML models of the number of DTP (Diphteria-tetanus-pertussis) vaccine doses (1, 2,3). Surprisingly, a colleague (statistician) thinks that this outcome should preferentially be treated as ordered or unordered multinomial categories rather than a count. This seems very intriguing. Finally, I am wondering about the most appropriate choice in this situation.
Many thanks for your valuable assistance.

[GeorgeLeckie]

Hi,

As the outcome can only take one of three values, treating it as an (ordered) categorical response sound reasonable.

However, as this question is more about modelling decisions rather than specifically about runmlwin, I think you might be better off posting this on the JISC multilevel list. That email list has a much wide range of subscribers who should be able to give you their opinions.

Best wishes

George