What are the classical logistic regression analysis and COX proportional hazard regression analysis? What is the difference and common between them?
Answer:
What are the classical logistic regression analysis and COX proportional hazard regression analysis? What is the...
4 & 5
QUESTION 4 What is a major difference between linear regression and logistic regression? a. The nature of the independent variable(s) b. The nature of the dependent variable c. The number of independent variables d. The number of dependent variables QUESTION 5 Which one of the following statistical tests would the researcher hope to have a non-significant result (p > .05) in a logistic regression analysis? a. The likelihood ratio test b. The logit step test C. The...
1. Our main concrete example of a proportional hazards regression model is Weibull regression. (a) What is the baseline hazard function for Weibull regression? Assume eo is part of the baseline hazard function (b) Suppose that the Weibul regression mode is the true model for a set of data. When we fit a proportional hazards regression model by maximum partial likeli- hood and estimate B1, what function of the Weibull regression model parameters are we estimating?
1. Our main concrete...
Of the analysis methods listed [Principal Component Analysis, Factor Analysis, Cluster Analysis, Discriminative Analysis, Logistic Regression, MANOVA, Canonical Correlation] The data consist of 130 observations generated by scores on a psychological test administered to Peruvian teenagers. For each of these teenagers the gender (male = 1, female =2) and socioeconomic status (low=1, Medium =2) were recorded. The scores were accumulated into five subscale sores labeled Independence, support, benevolence, conformity, and leadership.
1.When is logistic regression the appropriate model for modeling non-metric outcomes? 2.In what ways is logistic regression comparable to multiple regression? How does it differ? 3.Why are there two forms of logistic coefficients (original and exponentiated)?
For the following logistic regression model, the predictor variable “age” is a quantitative variable. Is there a large difference in the predicted probability of churn when comparing 30-year-old and 40-year-old customers? Yes; the difference of the predicted probability between these age groups is larger than 0.15 (15 percentage points) No; the difference of the predicted probability between these age groups is less than 0.15 (15 percentage points) 5-0.2*Age Predicted probability of churn - 5-0.2*Age Predicted probability of churn -
Logistic regression is what kind of learning algorithm?: a. supervised/classification b. unsupervised/classification supervised/regression d. unsupervised/regression C.
The following table contains statistics from a logistic
regression analysis for a study on intravenous drug use among high
school students in United States. Drug use is characterized as a
dichotomous variable, where 1 indicates that an individual has
injected drugs within the past year and 0 that he or she has not.
Factors that might be related to drug use are instruction about the
HIV in school (1 represents "had HIV education" and 0 represents
"did not have HIV...
9.) What characteristic of the outcome variable (Y) suggests that a logistic regression is a suitable methodology? a.) When the outcome is a continuous variable b.) When the outcome variable has a large variance c.) When the outcome is always positive d.) When the outcome is a dichotomous variable 10.) If, in a multiple regression of the price of a diamond against the two predictor variables, weight and color, the R2 of the regression was 0.985, then which of the...
Linear classifiers. Discuss the differences between LDA, Logistic Regression, separating hyperplanes, and the Optimal Soft-Margin Hyperplane. In what situations would you use each of the classifiers?
How regression analysis techniques help uncover relationships between variables? What are the seven (7) steps for avoiding the potential pitfalls of regression analysis?