ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2015, Vol. 47 ›› Issue (12): 1520-1528.doi: 10.3724/SP.J.1041.2015.01520

Previous Articles     Next Articles

A Regression Analysis Model of Ordinal Variable to Psychological Data

XU Peng1; QI Lu1; XIONG Jian2; YE Haosheng3   

  1. (1 Career Guidance Center, Guangzhou University, Guangzhou 510006, China) (2 School of Economics & Statistics, Guangzhou
    University, Guangzhou 510006, China) (3 Center for Mind and Brain, Guangzhou University, Guangzhou 510006, China)
  • Received:2015-02-09 Published:2015-12-25 Online:2015-12-25
  • Contact: YE Haosheng, E-mail:


Ordinal variables are the common form of categorical variables in random phenomenon. Ordinal data which is formed from the level of ordinal variables by sequencing scale measurement has been widely used in psychological research. Psychological data is a kind of data from randomized hidden variable, which seems to be noticeable but could not be touched such as degree of satisfaction, preference degree, cognition degree, sentiment perceptibility, behavioral level and so on. The mental impression is hard to be calculated. To be exposed for calculated ordinal data is a kind of judgment standard or decision threshold criteria of an individual psychological activity in implicit psychological data. When a certain degree of psychological feeling happens to be just between two adjacent thresholds, the individual would be given a numerical value like a scale to project this “Mirror mode” of the psychological decision threshold criteria. Meanwhile, people are always concerned about what factors or conditions decide the high-low of threshold value of these ordinal variables based on cognitive instinct. This sort of “Hopper model” which is used to study the factors affecting to the psychological decision threshold criteria is a typical regression model.
The paper proposes a multiple regression analysis model of ordinal variables based on the three problems involved in typical regression analysis “Hopper model” for ordinal variables. First, the ordinal variable indexes which can explain a psychological phenomenon are initially reduced in dimension by nor-parameter test method. Then, the effect indexes which have significant judgment standard are selected by using Probit ordinal regression. Finally, the probability of a psychological phenomenon happen is predicted and explained enormously by using Logistic regression model.
Based on the data of quality of work life for the college graduates, the forecasting is suggested and the simulation is done for the “Mirror mode” and the “Hopper model” of ordinal variables regression model. It is hoped that ordinal variables regression analysis models and statistical analysis methods would have wider applied value in study of psychological phenomena included cognition, emotion, behavior, economy, social life etc.

Key words: ordinal data, regression analysis, psychological data, quality of word life