You cannot convert it. Measurement scales are not equal.
But the most common type by far of ordinal logistic regression is the proportional hazards model, which assumes proportional hazards. That assumption might be violated, in which case, you might want to use multinomial logistic. The great advantages of linear regression are its ease of interpretation and its familiarity.
But it might be wrong. Ordinal logistic is more likely to be correct, but is less known and harder to understand. Multinomial logistic is even harder to understand, and is a very complex model, with many parameters to estimate.
Collapsing the variable will only very rarely be correct.
A Likert scale is composed of a series of four or more Likert-type items that represent similar questions combined into a single composite score/variable. Likert scale data can be analyzed as interval data, i.e. the mean is the best. First, acting as if Likert or other ordinal scales are continuous level data leads to many problems of interpretation (see the Appendix for a summary table of measurement scales and appropriate statistics). In true Likert scales (disagree to agree) the item can be seen as an interval variable with interval characteristics and quasi-normal distribution (this info also in the wikipedia page), so no problems in using a linear regression.
Do ordinal logistic regression and test the assumptions. Then if the assumptions are met, also do linear regression and compare the results by making a scatterplot of one set of predicted values vs.
If they are very similar YOU decide. Statistical analysis requires thought and judgment then go with linear regression. If the assumptions are NOT met, then also do multinomial logistic regression, and compare those two sets of results, opting for the simpler ordinal model if results are very similar.
I specialize in helping graduate students and researchers in psychology, education, economics and the social sciences with all aspects of statistical analysis. Many new and relatively uncommon statistical techniques are available, and these may widen the field of hypotheses you can investigate.
Graphical techniques are often misapplied, but, done correctly, they can summarize a great deal of information in a single figure.
I can help with writing papers, writing grant applications, and doing analysis for grants and research. Regression, logistic regression, cluster analysis, statistical graphics, quantile regression. You can click here to email or reach me via phone at Or if you want you can follow me on Facebook, Twitteror LinkedIn.A logistic regression is used for categorical predictors (0= no/no condition and 1=yes/condition); a linear regression is used for continuous predictors (e.g., Likert scale).
First, acting as if Likert or other ordinal scales are continuous level data leads to many problems of interpretation (see the Appendix for a summary table of measurement scales and appropriate statistics).
Jul 01, · Likert, Likert-type, and ordinal-scale responses are very popular psychometric item scoring schemes for attempting to quantify people’s opinions, interests, or perceived efficacy of an intervention and are used extensively in Physical Education and Exercise Science research.
May 01, · Responses to several Likert questions may be summed, providing that all questions use the same Likert scale and that the scale is a defendable approximation to an interval scale, in which case they may be treated as interval data measuring a latent variable.
Analyzing and Interpreting Data From Likert-Type Scales. understanding the interpretation and analysis of data derived from Likert scales is imperative for those working in medical education and education research.
(eg, t tests, analysis of variance, Pearson correlations, regression). 3 However, other experts assert that if there is an. In other words, a Likert scale is a special type of ordinal data scale. Ordinal data don’t require those properties (balance, neutral value, and equal spacing), but in my mind, Likert scales do require those properties, but don’t require specifically 5-points.