Calculate Kaplan-Meier curves for each disease group

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Reference no: EM131869951

Homework:

These problems use the Copelan bone marrow transplant dataset, available in the KMsury package.

Problem 1 - Use the cleaned bmt dataset (attached). Note that 'tp' is "time to platelet recovery".

Identify the (time, censor) pair for each of the following analyses:

a. Patient survival

b. Disease-free survival

c. Time to chronic graft versus host disease

d. Time to platelet recovery

Problem 2 - For patient post-transplant survival time,

a. Calculate Kaplan-Meier curves for each disease group. Plot the curves and comment on what you see.

b. Check whether these curves are different using the log-rank test.

c. What is the estimated one year survival of the three disease types? How does this compare with the estimates generated from a logistic regression model? You can use your results from Homework 3 if you generated the simple model (OneYearSurvival - group), but if you do, make sure that you are using the same data exclusions/modifications in each model.

Problem 3 - a. Build a multivariate Cox model for post-transplant survival. As before, manually build your best model, then run an automated variable selection algorithm and compare the results.

b. Compare your results to the logistic regression model from Homework 3. Which do you think is the better approach, and why?

c. Build another Cox model predicting disease-free survival. Are the predictors of disease-free survival different from those for patient survival?

Attachment:- Data Set.rar

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The task has been done in R language where libraries of the language are used to extract data. Libraries are used to make necessary calculations. After that explanation of the analysis are done to elucidate matter. This task is totally based on concepts hence any issues in understanding is probable.

Reference no: EM131869951

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