Level of Depression of College Students with Binary Logistic Regression Model Approximation in Covid-19 times

The objective of this research is to detect the level of depression that university students have because of Covid-19 using the binary logistic regression model and comparing with the linear model, it is of non-experimental design, cross-sectional descriptive type, with quantitative approach, The 9-item Patient Health Questionnaire (PHQ-9) was used with a population of 2185 respondents carried out during the month of May, the population is made up of university students from the Piura region chosen randomly, voluntarily and anonymously, resulting that the PHQ-9 measurement instrument is very good with a Cronbach's Alpha = 0. 885 and McDonald's W = 0.886, with 69.9% depression in university students, concentrated in 4 levels of depression, mild 39.7%, moderate 17.8%, severe 7% and very severe 5.3%. It was concluded that the PHQ-9 depression measurement instrument is adequate to measure depression in university students. In the discussion, it was possible to model the equation with the binomial logistic regression model, which results in better approximations than the linear model; this model is adequate to measure the level of depression in university students in the Piura region.