Stay poor. May 13, Can you all provide information on the intercept in a logistic model? Jake Cookie Scientist May 13, It has the same meaning as the intercept in a normal regression model.
The only difference is that things are on the logit scale. The intercept in a logistic model can be interpreted as the "baseline risk or odds". When you have covariate in the model, it represents the departure from the baseline increase or decrease in the odds of the event.
As many have said, you don't really need to interpret the intercept, especially in a logistic regression because more often than not it's being applied in a retrospective study so baseline risk isn't necessarily estimable to begin with. You must log in or register to reply here. Join Now. Ashish is the Editor-in-Chief of Analytics Insight. He brings over 16 years of experience in business research and analytics across different sectors.
Pre-Analysis Checks: There are a few common assumptions which are to be followed before performing the regression analysis. The dependent variable should be a scalar variable. Examples of scalar variables include height, salaries and age. The independent variables should be scalar or categorical variables sometimes referred as nominal variables. For example, gender is a categorical variable which has two categories- male and female. The data should not have any outliers.
This can be checked by using various methods including histogram and boxplot techniques. Also, the residuals of the regression line should be normally distributed. The relationship between the dependent and independent variables should be linear.
The B value for the intercept is the mean value of X1 only for the reference group. The mean value of X1 for the comparison group is the intercept plus the coefficient for X2. So I put together 6 situations in this follow up:. Is it logic that the accuracy of intercept is higher than that of the slope? Thanks so much for your explanations, Karen! I have a question: can I interpret the intercept Y in a regression model where my intercept is significant and two other predictors say X and Z , while X can never be zero but Z can be 0?
In my case Y is a change score. If the intercept is not equal to zero and significant can I infer from this that there is an overall change? Hi, I m analyzing logistic regression for my independent and dependent variables, form the regression coefficient I want to calculate risk score of the independent variables on dependent variable. When you eliminate it, you set it to 0. Everything is very open with a clear explanation of the issues. It was really informative.
Your site is very helpful. Many thanks for sharing! Thank you for this. May I suggest that it may be really helpful to use an example with real data to help explain how this works? For me and I expect for others too , it would make it much easier to understand. Is this is possible?? Can u make me clear with an easy example plz??? How to interpret the above? This usually occurs when none of the X values are close to 0.
The intercept of the regression line is just the predicted value for y, when x is 0. How do you find the regression equation? What is the Y intercept in regression analysis? The constant term in linear regression analysis seems to be such a simple thing. Also known as the y intercept, it is simply the value at which the fitted line crosses the y-axis. How do you interpret the slope of the least squares regression line?
The least squares regression line is of the same form as any linehas slope and intercept. What does the intercept represent? Is it reasonable to interpret the Y intercept? Interpreting the y-intercept of a regression line Sometimes the y-intercept can be interpreted in a meaningful way, and sometimes not. At times the y-intercept makes no sense.
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