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Can a dependent variable be a percentage?
In my data set the dependant variable is a percentage with a range 0 to 100. It can be interpreted as the probability or proportion as well. Data set shows an approximately normal distribution but the normality test is significant.
Can you do a regression with percentages?
One key consideration is the dependent variable. For linear models, the dependent variable doesn’t have to be normally distributed, but it does have to be continuous, unbounded, and measured on an interval or ratio scale. Percentages don’t fit these criteria.
What kind of distribution does logistic regression follow?
Logistic regression measures the relationship between the categorical dependent variable and one or more independent variables by estimating probabilities using a logistic function, which is the cumulative distribution function of logistic distribution.
Do you use percentage variable in logistic regression?
You have a percentage variable in a sense, but that’s just a way to display your data in a simplified manner. In another sense, you have a count of obese children out of a known total of kids. That is, you have binomial data. Thus, you should use logistic regression, using the counts of actual children.
Do you treat proportion as a dependent variable in regression?
If you can assume a linear model, it will be much easier to do, say, a complicated mixed model or a structural equation model. If it’s just a single multiple regression, however, you should look into one of the other methods. A second approach is to treat the proportion as a binary response then run a logistic or probit regression.
Do you use logit transformation in linear regression?
You should not use linear regression here, nor should you transform your data with the logit transformation. You have a percentage variable in a sense, but that’s just a way to display your data in a simplified manner. In another sense, you have a count of obese children out of a known total of kids.
How does the coefficient of an independent variable change?
Divide the coefficient by 100. This tells us that a 1% increase in the independent variable increases (or decreases) the dependent variable by (coefficient/100) units. Example: the coefficient is 0.198. 0.198/100 = 0.00198. For every 1% increase in the independent variable, our dependent variable increases by about 0.002.