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identify missing data
What Are the Methods to Handle Missing Data?
Several methods can be employed to handle missing data, each with its pros and cons:
Deletion Methods
: Removing cases with missing data, which can lead to a significant loss of valuable information.
Imputation Methods
: Filling in missing values using statistical techniques like
mean imputation
,
regression imputation
, or
multiple imputation
.
Model-Based Methods
: Using models that can handle missing data, such as
Maximum Likelihood Estimation
or
Bayesian methods
.
Frequently asked queries:
Why is Missing Data a Concern in Cancer Research?
What Types of Missing Data Exist?
How Can We Identify Missing Data?
What Are the Methods to Handle Missing Data?
What are the Challenges in Handling Missing Data?
What Are the Best Practices for Managing Missing Data?
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