I'm having a look at x-ray waiting times in an emergency department and how these relate to the day of the week and the time of day that requests are ordered. (Want to know if patients have to wait longer for their x-rays on weekends and at night compared with day shifts).
The waiting times have a significant right skew when plotted on a histogram. I divided the continuous variable "waiting times" into 5 categories (0-30 mins being the reference category). I also dummy coded the 6 days of the week and the "time of day" (which was divided into the 3 shifts of the day) into 0-the day in question and 1-the rest of the days of the week.
I performed univariate multinomial regression with waiting times as the dependent variable and each independent dummy variable in turn (omitting Saturday and Night shift from the analysis to act as "reference").
when I entered each variable independently, not one of them showed a significant relationship with x-ray waiting times. On multivariable multinomial regression, I found four variables were demonstrating p values less than 0.05, particularly with the waiting time category of 61-90 mins.
I wondered if anyone knew why this was? If there's a plausible explanation or whether I've made a mistake somewhere? Please help if you have any suggestions as I'm a complete stats amateur …
Best Answer
You don't really have more than one independent variable. You have multiple levels of a single categorical independent variable. You'll want to read threads like this one and the one linked at the bottom of that page, where the conversation is picked up in more detail. (btw, on that first page, I'd give more weight to @Frank's comment than to my answer.)