6) Suppose a multinomial regression model has two continuous explanatory variables ?1 and ?2 ,and they...

6) Suppose a multinomial regression model has two continuous explanatory variables ?1 and ?2 ,and they are represented in the model by their linear and interaction terms.
a) For a ? unit increase in ?1, derive the corresponding odds ratio that compares a category ? response to a category 1 response. Show the form of the variance that would be used in a Wald confidence interval.
b) Repeat this problem for a proportional odds regression model.

Expert Solution

milcah answered 1 year ago

suppose a regression model has two explanatory variables (x and z). If we add a new...

suppose a regression model has two explanatory variables (x and z). If we add a new variable to to the model (m), and this new variable is correlated to x and z, how would we use the new variable m to test the impact of variable x on our dependent variable y when z and m remain the same?

Multinomial logistic regression can be used on: a)Categorical predictor variables only. b)Both categorical and continuous predictor...

Multinomial logistic regression can be used on: a)Categorical predictor variables only. b)Both categorical and continuous predictor variables. c)Continuous predictor variables only. d)Ordinal predictor variables only.

Describe the potential advantages and disadvantages of incorporating additional explanatory variables in a multiple regression model.

CASE STUDY 2: Correlation and Regression are investigating the relationship between two continuous variables such as...

CASE STUDY 2: Correlation and Regression are investigating the relationship between two continuous variables such as height and weight, time and speed or the concentration of an injected drug and heart rate. a) In your opinion, discuss the importance of Correlation and Regression as a tools for analysis purposes. b) Find any correlation and regression that have been applied in business from the online platform. From the data you required to: i. State the Independent and Dependent Variable ii. Draw...

11.30 A simpler model. In the multiple regression analysis using all four explanatory variables, Theaters and...

11.30 A simpler model. In the multiple regression analysis using all four explanatory variables, Theaters and Budget appear to be the least helpful (given that the other two explanatory variables are in the model). (a) Perform a new analysis using only the movie’s opening-weekend revenue and IMDb rating. Give the estimated regression equation for this analysis. (b) What percent of the variability in USRevenue is explained by this model? (c) Test the null hypothesis that Theaters and Budget combined add...

1) True or False? In multinomial logistic regression analysis, the model fit is given by the...

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2. The estimated regression equation for a model involving two independent variables and 65 observations is:...

2. The estimated regression equation for a model involving two independent variables and 65 observations is: yhat = 55.17+1.2X1 -0.163X2 Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0, Sb1 = 0.33, Sb2 = 0.20. (16 points) a. Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 65 and X2 = 70. c. Compute R-square and Adjusted R-Square. d. Comment on the goodness of fit of the model. e. Compute MSR...

The following is a regression summary from R for a linear regression model between an explanatory...

The following is a regression summary from R for a linear regression model between an explanatory variable x and a response variable y. The data contain n = 50 points. Assume that all the conditions for SLR are satisfied. Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.1016 0.4082 -2.699 -------** x 2.2606 0.0981 ---- < 2e-16 *** (a) Write the equation for the least squares regression line. (b) R performs a t-test to test whether the slope is significantly...

Logistic regression predicts a 1._______, 2._, 3.________from one or more categorical or continuous predictor variables.

Logistic regression predicts a 1._____________, 2._____________, 3.______________from one or more categorical or continuous predictor variables.

1. You are given with the regression result that shows the regression model with k variables....

1. You are given with the regression result that shows the regression model with k variables. Answer the following parts: a) How do you tell that a certain variable is influential? b) Suppose the theoretical issue said there exist a linear constraint, how do you figure out the constraint holds? c) Suppose you have two sets of explanatory variables; how did you consider which set is the better one? d) What’s the meaning of R-squared? Should we always look for...

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