Question

What is the assumption of linearity in a logistic regression model? How can this be checked?

What is the assumption of linearity in a logistic regression model? How can this be checked?

Homework Answers

Answer #1

In case of simple linear regression there exists a linear relationship between dependant variable and the independant variables.

But in case of logistic regression there exists a linear relationship between log of dependant variable and the log of independant variables.

This linearity assumption can be verified by plotting the scattered plot and trendline for log of dependant variables and log of independant variables. This can be proved by finding the correlation coefficient for the above said graph and the value lies between -1 and 1

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
What are some of the violations of the linearity assumption in the multiple linear regression model...
What are some of the violations of the linearity assumption in the multiple linear regression model and how can we correct those violations? Mainly focus on how to correct them by stating the violations.
What does the exponent of the regression coeffcient, exp(B), represent in a logistic regression model?
What does the exponent of the regression coeffcient, exp(B), represent in a logistic regression model?
What types of predictor variables are acceptable to use in a logistic regression model? Only quantitative...
What types of predictor variables are acceptable to use in a logistic regression model? Only quantitative predictor variables are acceptable to use as predictor variables in logistic regression models Only dummy variables are acceptable to use as predictor variables in logistic regression models Both quantitative and dummy variables are acceptable to use as predictor variables in logistic regression models
Can any linear regression model be checked for model adequacy by statistical testing for lack of...
Can any linear regression model be checked for model adequacy by statistical testing for lack of fit or goodness of fit? Why or why not? Please provide your answer with detailed justification
What is logistic regression? When should we use logistic regression instead of linear regression? Why cannot...
What is logistic regression? When should we use logistic regression instead of linear regression? Why cannot we use linear regression where logistic regression is used? Provide the generalized multiple logistic regression equation.
In a regression analysis, what assumption can be checked with a normal probability plot of the...
In a regression analysis, what assumption can be checked with a normal probability plot of the residuals, and what should one look for in such a plot? (A) x and y are correlated. Look for a straight line pattern. (B) The residuals all have the same variance. Look for a straight line pattern. The vertical variation in the plot should be roughly constant throughout the whole range of fitted values. (C) The residuals follow a normal distribution. Look for a...
What is it and how to test the goodness of fit for a logistic model?
What is it and how to test the goodness of fit for a logistic model?
In a logistic regression model, an independent variable X must have binary outcomes. True or False
In a logistic regression model, an independent variable X must have binary outcomes. True or False
I am working on a logistic regression model in python where I am using NBA data...
I am working on a logistic regression model in python where I am using NBA data to predict whether a player is a good rebounder or not based on various predictor variables. And my reg.coef is = array([[-1.50137324, -1.77554507, -1.73097902, 0.2568646 , 0.73556433, 0.00773832, -0.30204417, 0.26622955, 0.21256178]]) interpret the coefficients of your logistic regression model shown above
Assume one of the explanatory variable (named X1) in your logistic regression is a categorical variable...
Assume one of the explanatory variable (named X1) in your logistic regression is a categorical variable with the following levels: low, average and high, and another explanatory variable (named X2) is also categorical with the following levels: Sydney, Melbourne, Hobart and Brisbane. Explain how you will use them in developing your logistic regression model. How many coefficients you will have in your final model?
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT