You may have noticed in the data set in Table 8.9 that many of the variables have
Question:
You may have noticed in the data set in Table 8.9 that many of the variables have missing values. In fact, only eight of the rows have measures on all six predictor variables. Data sets with missing values are not uncommon and tend to be due to individuals not providing responses to all the questions in a survey. One strategy that can be used to deal with missing values is imputation. Imputation entails imputing a value in place of each missing value. One typical imputation strategy would be to replace all of the missing values of a variable with the mean of the variable or the median of the variable.
a. For the data in Table 8.9, use the strategy of imputing the mean for the missing values for each of the variables that have missing data, and then run a regression analysis.
b. Comment on what you think has changed by imputing the mean for the missing values of each variable.
c. For the data in Table 8.9, use the strategy of imputing the median for the missing values for each of the variables that have missing data, and then run a regression analysis \((\alpha=0.10)\).
d. Comment on what you think has changed by imputing the median for the missing values of each variable.
e. Do you think imputing the mean or the median is more appropriate for this problem?
Table 8.9
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