Combining and comparing many imputation models

To evaluate the different imputation methods, we need to put them into a single dataframe. Next, you will compare three different approaches to handling missing data using the dataset, oceanbuoys.

The first method is using only the completed cases and is loaded as ocean_cc.
The second method is imputing values using a linear model with predictions made using wind and is loaded as ocean_imp_lm_wind.

You will create the third imputed dataset, ocean_imp_lm_all, using a linear model and impute the variables sea_temp_c, air_temp_c, and humidity using the variables wind_ew, wind_ns, year, latitude, longitude.

You will then bind all of the datasets together (ocean_cc, ocean_imp_lm_wind, and ocean_imp_lm_all), calling it bound_models.

Create an imputed dataset named ocean_imp_lm_all using a linear model and impute the variables sea_temp_c, air_temp_c, and humidity using the variables wind_ew, wind_ns, year, latitude, longitude.
Bind all of the datasets together into the same object, calling it bound_models.

Exercise

Combining and comparing many imputation models

Instructions