Statistical method to analyze data with one continuous IV and two categorical DVs

Hi,

I'm trying to find the right statistical method to analyze data with one continuous independent variable and two categorical dependent variables.

IV is Perceived Usefulness (scale coded: 1,2,3,4, or 5)
DV is Usage (scale coded:
Item 1: (1) Never, (2) About once, (3) 2-3 times, (4) 4-5 times, and (5) More than 5 times a day.
Item 2 (1) None, (2) Less than 1 hour, (3) 1-2 hours, (4) 2-3 hours, and (5) More than 3 hours. )
Please, no links to general discussion sites - I've been looking this up for hours.

Wouldn't the IV be ordinal (and therefore categorical) rather than continuous? Or are there any number of values possible between 1,2,3,4 and 5 for perceived usefulness? I am currently doing a stats subject at uni so I am quite interested in this question.

Perceived Usefulness has always been treated as continuous, in the literature I've seen, even though there are only 5 to 7 discrete choices on a Likert scale. Some new surveys use a slider to get real continuous data.

Ah yes, I can see why now. A perceived usefulness of 3.75 would be a perfectly valid result, whereas there is no value possible between two categories.

Hmmm. Is there some way you can combine the two DVs (say, with a matrix) and then compare the matrix value with the IV? I'm not sure if that's even a valid approach strictly statistically speaking.

But hey, you came here for an answer, not more questions, so don't feel you have to keep responding - you clearly know what you are doing.

0

At Springboard, we know how to get you a job in data science. With Springboard’s Data Science Career Track, you’ll master data science with a curriculum built by industry experts. You’ll work on real projects, and get 1-on-1 mentorship from a data scientist.

I think you may be right about this being muddy. I can think of lots of ways to compare variables, but not three at once in that combination. There must be a way to combine the two DVs in such a way that you can still make sense of the data, since I am assuming what you are trying to do is compare the perceived usefulness with the amount of time spent using the resource? This is what I meant before about using a matrix to combine the two DVs into a set of scores - The columns would be Item 1 and the rows would be Item 2, so a score of 43 would be 4-5 time for 1-2 hours.

This looks like a simple multivariate regression analysis problem.
Make sure you check for multicollinearity.

You could also just do two normal regression analysis problems, use one DV as the DV and the other as a second IV and do the calculation and then swap them and do it again.

You asked for a statistical method to analyze two DVs. Multivariate linear regression is what I would use. You can do a Google search for Analysis of Multivariate Categorical Variables and you will see several other methods (and books and scholarly articles and whatnot).

Are you ready to take your data science career to the next step, or break into data science? With Springboard’s Data Science Career Track, you’ll master data science topics, have personalized career guidance, weekly calls with a data science expert, and a job guarantee.