Question

In: Statistics and Probability

Discuss the applications of Binary Logistic Regression in Clinical Research using the case study given in the(Application of Binary Logistic Regression in Clinical Research)

 

Discuss the applications of Binary Logistic Regression in Clinical Research using the case study given in the(Application of Binary Logistic Regression in Clinical Research) in a brief manner with a maximum length of two pages

 

Solutions

Expert Solution

trategic relapse

It is utilized in different fields, including AI, most restorative fields, and sociologies.

For instance, the Trauma and Injury Severity Score (TRISS), which is generally used to anticipate mortality in harmed patients, was initially created by Boyd et al. utilizing strategic relapse. Numerous other therapeutic scales used to survey seriousness of a patient have been created utilizing calculated relapse.

  • It is additionally utilized in advertising applications, for example, expectation of a client's penchant to buy an item or end a membership, and so forth. In financial aspects it tends to be utilized to foresee the probability of an individual's being in the work constrain, and a business application is anticipate the probability of a property holder defaulting on a home loan. Contingent irregular fields, an augmentation of strategic relapse to consecutive information, are utilized in normal language preparing.
  • Another model may be to foresee whether an Indian voter will cast a ballot BJP or Trinamool Congress or Left Front or Congress, in light of age, pay, sex, race, condition of habitation, cast a ballot in past decisions, and so on. The procedure can likewise be utilized in designing, particularly for anticipating the likelihood of disappointment of a given procedure, framework or item.
  • Calculated relapse might be utilized to foresee the danger of building up a given malady (for example diabetes; coronary illness), in light of watched qualities of the patient (age, sex, weight file, aftereffects of different blood tests, and so on.).

Related Solutions

What is binary logistic regression, and how to use it?
What is binary logistic regression, and how to use it?
What is binary logistic regression, and how to use it?
What is binary logistic regression, and how to use it?
If a dependent variable is binary, is it optimal to use linear regression or logistic regression?...
If a dependent variable is binary, is it optimal to use linear regression or logistic regression? Explain your answer and include the theoretical and practical concerns associated with each regression model. Provide a business-related example to illustrate your ideas.
What assumptions must be satisfied before a binary logistic regression can be performed?
What assumptions must be satisfied before a binary logistic regression can be performed?
Fit a binary logistic regression model with admission decision as the dependent variable, GRE and GPA...
Fit a binary logistic regression model with admission decision as the dependent variable, GRE and GPA as the independent variables. Evaluate the goodness of fit of the model. Determine the significance of independent variables. Interpret odds ratios for independent variables. State the binary logistic regression equation. Evaluate the classification accuracy of the model. Check if the residuals are independent. Admit GRE GPA 0 790 1 1 370 0 1 480 1 1 580 1 1 620 1 0 740 0...
In the exer- cise, you will implement logistic regression algorithm using SGA, similar to the logistic...
In the exer- cise, you will implement logistic regression algorithm using SGA, similar to the logistic regression algorithm that you have seen in class. You will work with the datasets attached to the assignment and complete the lo- gisticRegression.py file to learn the coefficients and predict binary class labels. The data comes from breast cancer diagnosis where each sample (30 features) is labeled by a diagnose: either M (malignant) or B (be- nign) (recorded in the 31-st column in the...
Discuss the application of multiple linear regression
Discuss the application of multiple linear regression
Discuss the application of simple linear regression
Discuss the application of simple linear regression
For application case 4.6 – Data Mining Goes to Hollywood, describe the research study, the methodology,...
For application case 4.6 – Data Mining Goes to Hollywood, describe the research study, the methodology, the results and the conclusion. Data Mining Goes to Hollywood: Predicting Financial Success of Movies Predicting box-office receipts (i.e., financial success) of a particular motion picture is an interesting and challenging problem. According to some domain experts, the movie industry is the “land of hunches and wild guesses” due to the difficulty associated with forecasting product demand, making the movie business in Hollywood a...
1) True or False? In multinomial logistic regression analysis, the model fit is given by the...
1) True or False? In multinomial logistic regression analysis, the model fit is given by the value of R-squared. In linear regression analysis, the overall significance test is an F test. In logistic regression analysis, the overall significance test is an F test. When building a model for regression analysis, the type of data for the outcome variable guides you to choose linear, logistic, or multinomial logistic. Two variables that covary might not have a causal relationship. Causation implies correlation....
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT