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I have a questionnaire of a 3-point Likert scale for an overall evaluation for a service, and several detailed attributes evaluation of that service. For example: Overall Evaluation (1-3), then Cleanliness (1-3) Comfort (1-3) Privacy (1-3) ..etc I am looking for a way to find what are the most important variables (attributes) that have the highest impact on overall evaluation. Is ordinary regression helping?

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Normally data from such Likert scales are interpreted as holding ordinal but not interval scaled information, and the linearity assumption in standard linear regression will be problematic for sure with a response variable that only has 3 output values (it may be OK with Likert explanatory variables but then it may not, depending on the data).

There's ordinal regression for response variables that are ordinal. This normally assumes that the explanatory variables are quantitative. You can run it with ordinal x-variables and check whether the implied linear assumption looks OK. Another option is ordinal-ordinal regression.

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